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：了解脊柱裂中的遗传复杂性在神经管缺陷（NTD）中人类结构畸形。多达70％的SB病例归因于遗传易感性环境在有危险的人中促成SB表现。尽管对遗传因素进行了数十年的研究，小鼠模型中的NTD基础，转化为人类风险评估和SB病例的改善难以捉摸。这在很大程度上归因于遗传研究中典型候选基因方法的局限性人类NTD。在这里，我们在整个基因组中的突变伯嫩突变的综合系统生物学方法序列（WGS）分析是通过质疑蛋白质来照亮人类SB的分子途径编码和非编码区域，并介绍机器学习以一种不可靶的方式选择的基因 SB歧视潜力基于稀有的，可能已删除的蛋白质编码变体基因富集。该项目扩展了我们全面的基因组工作，在最近收集的200个中产生了新的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基因 - 基因相互作用导致SB，并提高对这一复杂先天缺陷的机械理解。 AIM 1使用家庭研究和系统生物学方法来寻求具有从头传输或从头罕见的基因暗示SB缔合的变体。这开始评估父母与从头开始的“第二击”，捐款到SB。分析包括蛋白质编码和非编码序列单核苷酸变体（SNV），稀有拷贝数字变体（RCNV）和最先进的计算探针利用基因组3D结构。 AIM 2测试这些检测到的基因的功能显着性和相互作用，以及：（a）使用 CRISPR编辑了新型SOSR，3-D体外方法中的同基因杂合性人干细胞评估增殖，自组织和分化，（b）测试这些突变的转录影响在诱变的细胞中使用散装和单细胞RNASEQ。 AIM 3检查使用现有和CRISPR-的双重/多杂合蛋白编码突变编辑的小鼠测试基因相互作用对NT闭合的组织学和基因表达影响。我们的计算方法在现场具有高度创新性，使用机器学习来构建网络人类SB风险的模型。然后，我们将先进技术应用于这些遗传风险的功能测试与等源性对照相比，包括人类干细胞的基因编辑，以及细胞和小鼠的模型基于系统的假设测试体外和体内，以及细胞类型表达的评估这些变体引起的变化。我们研究的见解将为精确医学能力铺平道路个性化NTD预防和护理家庭以及成千上万的SB患者。