Understanding Genetic Complexity in Spina Bifida

了解脊柱裂的遗传复杂性

基本信息

批准号：
10750235
负责人：
RICHARD H. FINNELL
金额：
$ 73.77万
依托单位：
WEILL MEDICAL COLL OF CORNELL UNIV
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：
2023-09-12 至 2028-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10750235
关键词：
3-Dimensional Adhesions Admixture Affect Apical Binding Sites Biological Biological Process Biological Testing Brain Breeding CRISPR/Cas technology Candidate Disease Gene Caring Case/Control Studies Cells Cellular biology Child Clustered Regularly Interspaced Short Palindromic Repeats Code Collaborations Complex Computational Biology Computing Methodologies Congenital Abnormality Copy Number Polymorphism Couples DNA sequencing Data Disease Embryo Enhancers Environmental Risk Factor Equilibrium Etiology Evaluation Event Exons Failure Family Family Study Folic Acid Food Supply Frequencies Gene Combinations Gene Expression Genes Genetic Genetic Epistasis Genetic Predisposition to Disease Genetic Risk Genetic Transcription Genetic Variation Genetic study Genome Genomic Segment Genomic approach Genomics Goals Hand Heterozygote Histologic Human Human Genome Impairment In Vitro Individual Inherited MAX gene Machine Learning Maps Meningomyelocele Methods Modeling Molecular Mus Mutagens Mutation Natural Immunity Nerve Nervous System Trauma Neural Tube Closure Neural Tube Defects Neural tube Organogenesis Organoids Parents Pathogenesis Pathway interactions Patients Pattern Population Population Control Pregnancy Prevention Proliferating Proteins Publishing Regulator Genes Research Risk Risk Assessment Sampling Sampling Biases Selection Bias Sequence Analysis Single Nucleotide Polymorphism Site Spinal Dysraphism Structural defect System Systems Biology TP53 gene Technology Testing Untranslated RNA Validation Variant Vertebral column case control cell type cohesin cohort comparison control constriction de novo mutation disability disorder risk effective therapy folic acid supplementation fortification frontier gene function gene interaction genetic variant genome analysis genome editing human embryonic stem cell human model human stem cells improved in vitro Model in vitro testing in vivo induced pluripotent stem cell innovation insight intrauterine environment learning strategy mouse model multiple datasets network models novel novel strategies precision medicine prevent progenitor rare variant self organization single-cell RNA sequencing three dimensional structure transcription factor transcriptome translation to humans transmission process whole genome

项目摘要

ABSTRACT: UNDERSTANDING GENETIC COMPLEXITY IN SPINA BIFIDA Among neural tube defects (NTDs), myelomeningocele (spina bifida:SB), is a devastating but survivable, human structural malformation. Up to 70% of SB cases are attributed to genetic predisposition, with intrauterine environment precipitating SB manifestation in those at risk. Despite decades of research into genetic factors that underlie NTDs in mouse models, translation to human risk assessment and amelioration of SB cases remain elusive. This is largely attributable to limitations of the typical candidate gene approaches used in genetic studies of human NTDs. Here, our comprehensive systems biology approach to mutation burden in whole genome sequence (WGS) analyses is illuminating molecular pathways to human SB through interrogation of protein coding and non-coding regions, and introduces machine learning to select, in an untargeted fashion, genes with SB discriminatory potential based on gene enrichment by rare, likely deleterious protein coding variants. The project extends our comprehensive genomic effort, generating new WGS on 200 recently collected patient-parent trio (600 genomes) samples. Studies aim to identify specific gene drivers of human SB, illuminate gene-gene interactions leading to SB, and improve mechanistic understanding of this complex birth defect. Aim 1 uses family study and systems biology approaches to seek genes with transmitted or de novo rare variants suggesting SB-association. This begins assessment of parental vs de novo, “second hit”, contributions to SB. Analyses include protein-coding and noncoding sequence single nucleotide variants (SNVs), rare copy number variants (rCNVs), and state-of-the art computational probes leveraging genome 3D structure. Aim 2 tests the functional significance and interactions of these detected genes and variations to: (a) use CRISPR edited isogenic, double heterozygous human stem cells in a novel SOSRS, 3-D in vitro method to evaluate proliferation, self-organization, and differentiation, (b) test the transcriptional impact of these mutations using bulk and single cell RNAseq in mutagenized cells. Aim 3 examines double/multiple-heterozygous protein coding mutations using existing and CRISPR- edited mice to test the histological and gene expression impact of gene interactions on NT closure. Our computational approaches are highly innovative in the field, using machine learning to build network models of human SB risk. We then apply advanced technology for the functional testing of these genetic risk models, including gene editing of human stem cells, compared to isogenic controls, and mice for cellular and systems based hypothesis testing in vitro and in vivo, along with evaluation of the cell-type gene expression changes induced by these variants. Insights from our studies will pave the way for a precision medicine capability to individualize NTD prevention and care for families and the hundreds of thousands of patients living with SB.

摘要：了解脊柱裂的遗传复杂性在神经管缺陷 (NTD) 中，脊髓脊膜膨出（脊柱裂：SB）是一种破坏性但可生存的疾病，高达 70% 的 SB 病例归因于遗传倾向，且为宫内胎儿。尽管对遗传因素进行了数十年的研究，但环境仍会促使高危人群表现出 SB。小鼠模型中的 NTD 是 NTD 的基础，转化为人类风险评估和 SB 病例的改善仍然存在这主要归因于遗传研究中使用的典型候选基因方法的局限性。在这里，我们针对全基因组突变负担的综合系统生物学方法。序列 (WGS) 分析通过研究蛋白质阐明人类 SB 的分子途径编码和非编码区域，并引入机器学习以非目标方式选择基因 SB 歧视潜力基于罕见的、可能有害的蛋白质编码变体的基因富集。该项目扩展了我们全面的基因组工作，在最近收集的 200 个数据上生成了新的全基因组测序 (WGS) 患者-父母三人组（600 个基因组）样本研究旨在识别人类 SB 的特定基因驱动因素，阐明这一点。导致 SB 的基因间相互作用，并提高对这种复杂出生缺陷的机制的理解。目标 1 使用家族研究和系统生物学方法来寻找具有遗传性或新生罕见性的基因建议 SB 协会这开始评估父母与从头的“第二次打击”贡献。 SB 的分析包括蛋白质编码和非编码序列单核苷酸变异 (SNV)、稀有拷贝。数字变异 (rCNV) 和利用基因组 3D 结构的最先进的计算探针。目标 2 测试这些检测到的基因和变异的功能意义和相互作用：(a) 使用 CRISPR 在一种新型 SOSRS、3-D 体外方法中编辑同基因、双杂合人类干细胞评估增殖、自组织和分化，(b) 测试这些突变的转录影响在诱变细胞中使用批量和单细胞 RNAseq。目标 3 使用现有的和 CRISPR 检查双/多个杂合蛋白编码突变编辑小鼠以测试基因相互作用对 NT 闭合的组织学和基因表达影响。我们的计算方法在该领域具有高度创新性，使用机器学习来构建网络然后，我们应用先进技术对这些遗传风险进行功能测试。模型，包括与同基因对照相比的人类干细胞的基因编辑，以及细胞和小鼠的基因编辑基于系统的体外和体内假设检验，以及细胞类型基因表达的评估这些变异引起的变化将为精准医疗能力铺平道路。为家庭和数十万 SB 患者提供个体化的 NTD 预防和护理。