Advancing discovery for developmental disorders - expanded analysis of the DDD-Africa resource

推进发育障碍的发现 - DDD-非洲资源的扩展分析

• 批准号: 10712946
• 负责人: Zane Lombard
• 金额: $ 25万
• 依托单位: WITS HEALTH CONSORTIUM (PTY), LTD
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10712946
• 关键词: Acceleration; Address; Affect; Africa; African; American; Artificial Intelligence; Awareness; Birth; Caring; Cessation of life; Childhood; Chronic; Clinical; Clinical Data; Collaborations; Communicable Diseases; Complex; Computer software; Country; DNA; DNA Methylation; Data; Data Science; Democratic Republic of the Congo; Diagnosis; Diagnostic; Disability phenotype; Disease; Ecosystem; Ethics; Genetic; Genetic Heterogeneity; Genetic Predisposition to Disease; Genetic Services; Genomic approach; Genomics; Genotype; Health; Healthcare; Individual; Infant Mortality; Intellectual functioning disability; Knowledge; Knowledge Discovery; Medical; Medical Genetics; Morbidity - disease rate; Neonatal Mortality; Parents; Participant; Patients; Phenotype; Population; Prevalence; Public Domains; Rare Diseases; Reporting; Research; Resource Sharing; Resources; Sampling; Signs and Symptoms; South Africa; Survivors; Syndrome; Techniques; Time; Translating; Variant; Work; clinical heterogeneity; developmental disease; disability; early childhood; epidemiologic data; exome; exome sequencing; experience; genetic disorder diagnosis; genome resource; genome-wide analysis; global health; health data; improved; indexing; innovation; methylation pattern; mortality; neglect; novel; phenotypic data; population based; tool

Developmental disorders (DD) are severe and chronic disabilities that often leads to early childhood death, or long-term morbidity in the survivors. Due to the high burden of infectious disease in many African countries, active research into rare diseases such as DD has often been neglected. The genetic aetiology of DD is complex as DD syndromes are marked by both clinical- and genetic heterogeneity. The Deciphering Developmental Disorders in Africa study (DDD-Africa) was initiated to address this knowledge gap, and the resource that was built holds the potential for much discovery, especially by catalyzing new collaborations and through the application of data science approaches. We therefore propose to use the clinical information, genetic data, and DNA resources from the DDD-Africa study to investigate the following hypotheses: 1. An exome-based CNV calling workflow that incorporates different tools, will identify putative disease- causing structural variants, and increase the diagnostic yield for DD-ID patients. 2. Identifying genome-wide DNA methylations patterns will assist in diagnosing genetically unsolved African DD-ID patients. 3. Phenotype-aware, artificial intelligence software can improve genotype-phenotype correlation in African DD-ID patients. Through this study, we will increase the diagnostic yield of DD-ID in African patients and broaden the knowledge discovery potential for rare diseases in Africa. This work will furthermore increase health data science capacity in Africa and create an ecosystem that can provide local solutions for rare diseases such as DD in Africa.

发育障碍（DD）是严重和慢性残疾，通常导致幼儿死亡， 或幸存者的长期发病率。由于许多非洲的传染病负担很大 国家对罕见疾病（例如DD）的积极研究经常被忽略。遗传病因 DD是复杂的，因为DD综合征是由临床和遗传异质性标记的。解密 非洲研究（DDD-AFRICA）的发展障碍是为了解决这一知识差距，而 建立的资源具有许多发现的潜力，尤其是通过催化新的合作 并通过应用数据科学方法。因此，我们建议使用临床 来自DDD-Africa研究的信息，遗传数据和DNA资源，以调查以下 假设： 1。基于外显子的CNV调用工作流，结合了不同的工具，将确定推定的疾病 - 引起结构变异，并增加DD-ID患者的诊断产率。 2。识别全基因组DNA甲基化模式将有助于诊断遗传无法解决 非洲DD-ID患者。 3。表型感知，人工智能软件可以改善基因型 - 表型相关性 非洲DD-ID患者。 通过这项研究，我们将增加非洲患者DD-ID的诊断产量，并扩大 知识发现潜在的非洲罕见疾病。这项工作将进一步增加健康数据 非洲的科学能力，并创建一个生态系统，可以为罕见疾病提供当地解决方案 作为非洲的DD。