Identify the heterogeneity and commonality of chronic overlapping pain conditions (COPCs) through phenotypic and genomic perspectives

通过表型和基因组观点识别慢性重叠疼痛病症 (COPC) 的异质性和共性

• 批准号: 10525765
• 负责人: Jungwei Wilfred Fan
• 金额: $ 25.19万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10525765
• 关键词: Adult; Algorithms; All of Us Research Program; American; Anatomy; Bioinformatics; Biological; Biometry; Catalogs; Characteristics; Chronic; Classification Scheme; Clinical; Clinical Data; Clinical Informatics; Code; Cohort Studies; Controlled Study; Craniofacial Pain; Data; Data Science; Data Set; Development; Diagnosis; Diagnostic; Disease; Elements; Epidemiology; Etiology; Event; Foundations; Functional disorder; Future; Genes; Genetic; Genome; Genomics; Genotype; Genotype-Tissue Expression Project; Goals; Graph; Heterogeneity; Informatics; Irritable Bowel Syndrome; Knowledge; Measurement; Medicine; Methods; Mining; National Human Genome Research Institute; Natural Language Processing; Neuroimmune; Neurosecretory Systems; Noise; Observational Study; Ontology; Outcome; Pain; Pain management; Pathway interactions; Patients; Pattern; Pharmaceutical Preparations; Phenotype; Population; Prevalence; Protocols documentation; Public Health; Quantitative Trait Loci; Records; Reproducibility; Research; Resolution; Resources; Risk; Sample Size; Semantics; Subgroup; Surface; Taxonomy; Temporomandibular Joint Disorders; Testing; Therapeutic; Translational Research; Untranslated RNA; Work; base; biobank; chronic pain; clinical data warehouse; comorbidity; cost; craniofacial; design; drug repurposing; effective therapy; functional genomics; gastrointestinal; genome wide association study; genome-wide; genomic data; health record; innovation; insight; interdisciplinary approach; knowledge base; multiple data sources; novel; orofacial; patient subsets; phenome; population based; precision medicine; statistics; stressor; success; symptomatology; treatment strategy

PROJECT SUMMARY/ABSTRACT With an estimated prevalence of 20% in American adults and annual costs above $500 million, chronic pains pose a high toll to public health. Many patients developed chronic overlapping pain conditions (COPCs), where craniofacial pains like temporomandibular disorder (TMD) represent a unique component that co-occurs frequently with other chronic pains including irritable bowel syndrome (IBS). Not only do the comorbidities complicate pain management, but the etiology of COPCs remains unclear. Heterogeneity exists within and across COPCs, so mechanism-based classification schemes are needed to identify safe and effective therapies for distinct subgroups of patients. However, existing research surrounding COPC taxonomy has not fully integrated phenotypic and genotypic data at the population level. Reliance on disease-specific study cohorts seriously limited the sample size and diversity. On the other hand, informatics and data science have advanced secondary use of biomedical data, presenting a strong alternative to hypothesis-driven, controlled studies. We propose to elicit COPC subgroups by mining three distinct population-based clinical datasets and imputing the biological underpinnings of co-occurring COPCs by using functional genomic knowledge bases. Our approach consists of two aims: 1) Identify COPC subgroups and other commonly associated phenotypes from rich longitudinal clinical data and notes, including over one million patients in the Rochester Epidemiology Project. The clinical datasets will be computationally screened for COPCs and other co-occurring phenotypes based on diagnosis codes and natural language processing. We will identify statistically significant COPC comorbidities and progression trajectories using novel and tailored statistics. The discovered trajectories will be clustered into subgroups using cutting-edge graph clustering algorithms. The patients will be assigned to the best matched subgroups, for which additional phenotypic characteristics of each group will be determined by least absolute shrinkage and selection operator. 2) Impute biological underpinnings for comorbid COPCs by integrating phenotypic, genetic, and genomic data in biobanks and biorepositories. We will conduct genome-wide and phenome-wide association studies based on the diagnoses and genotypes from the UK Biobank and All of Us Research Program, leading to identification of additional genotypes that are associated with the COPCs and beyond those in the NHGRI-EBI GWAS catalog. We will apply our information-theoretic framework to impute the functional similarity and shared biological mechanisms across COPCs by using GTEx expression quantitative trait loci data and gene ontology annotations. The findings of shared mechanisms among COPCs will provide novel insight into the genetic factors, particularly in noncoding regions, and functional linkages that are pivotal to developing applications such as drug repurposing for COPCs. The two aims corroborate each other across the genome-phenome boundary to unveil interpretable subgroups that will advance precision medicine for COPCs.

项目摘要/摘要 美国成年人估计患病率为20％，年每年成本超过5亿美元，慢性疼痛 对公共卫生造成了很大的损失。许多患者患有慢性重叠疼痛状况（COPC），其中 颅面疼痛（如颞下颌疾病（TMD））代表了共同出现的独特成分 经常出现其他慢性疼痛，包括肠易激综合症（IBS）。不仅合并症 使疼痛管理复杂化，但COPC的病因尚不清楚。异质性存在于和 在整个COPC之间，因此需要基于机制的分类方案来识别安全有效的疗法 对于不同的患者亚组。但是，围绕COPC分类法的现有研究尚未完全 人口水平的综合表型和基因型数据。依赖特定疾病的研究队列 严重限制样本量和多样性。另一方面，信息学和数据科学已经提高了 生物医学数据的次要使用，为假设驱动的对照研究提供了强有力的替代方法。我们 建议通过挖掘三个不同的基于人群的临床数据集并归纳 通过使用功能基因组知识库的共发生COPC的生物基础。我们的方法 由两个目的组成：1）识别富人的COPC亚组和其他常见的表型 纵向临床数据和注释，包括罗切斯特流行病学项目中超过一百万患者。 临床数据集将根据COPC和其他基于COPC的计算筛选 诊断代码和自然语言处理。我们将确定具有统计学意义的COPC合并症 以及使用新颖和量身定制的统计数据的进展轨迹。发现的轨迹将聚集到 使用尖端图集群算法的子组。患者将被分配给最佳匹配 亚组，为此，每组的其他表型特征将由最少绝对确定 收缩和选择操作员。 2）通过整合合并COPC的生物基础 生物库和生物膜的表型，遗传和基因组数据。我们将进行全基因组，并 基于英国生物库和我们所有人的诊断和基因型的现象整个关联研究 研究计划，导致鉴定与COPC相关的其他基因型 超越NHGRI-EBI GWAS目录中的那些。我们将应用我们的信息理论框架 通过使用GTEX表达定量，跨COPC的功能相似性和共享的生物学机制 特质基因座数据和基因本体论注释。 COPC中共享机制的发现将提供 对遗传因素的新洞察，特别是在非编码区域，以及与之关键的功能联系 开发应用程序，例如对COPC的药物重新利用。两者的目标在整个地方互相证实 基因组 - 表现边界，以揭示将推出COPC精确药物的可解释亚组。