Identification and characterization of children with asthma-associated comorbidities through computational and immune phenotyping

通过计算和免疫表型分析患有哮喘相关合并症的儿童的识别和特征分析

• 批准号: 10337267
• 负责人: YOUNG J JUHN
• 金额: $ 79.14万
• 依托单位: MAYO CLINIC ROCHESTER
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2025-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10337267
• 关键词: Address; Adult; Algorithms; Antigens; Appendicitis; Asthma; Autoimmune Diseases; Birth; CD3 Antigens; Caregivers; Caring; Celiac Disease; Cell Cycle; Centers for Disease Control and Prevention (U.S.); Characteristics; Child; Childhood Asthma; Chronic Disease; Clinic; Clinical; Clinical Research; Cohort Studies; Communicable Diseases; Computerized Medical Record; County; Cross-Sectional Studies; Data; Development; Diabetes Mellitus; Disease; Early identification; Enrollment; Family history of; Future; Goals; Health; Herpes zoster disease; Immune; Immunity; Impairment; Infection; Inflammatory; Knowledge; Longitudinal Studies; Measurement; Measures; Memory; Natural Immunity; Natural Language Processing; Outcome; Patient-Focused Outcomes; Patients; Pediatric Hospitals; Phenotype; Pneumococcal Infections; Pneumococcal Pneumonia; Pneumonia; Population; Population Surveillance; Records; Reproducibility; Research; Research Design; Research Personnel; Respiratory Tract Infections; Rheumatoid Arthritis; Risk; Risk Factors; Sampling; Sioux Falls; Site; Subgroup; Symptoms; T-Lymphocyte; Time; Time Management; United States; Work; adaptive immunity; asthmatic; base; cohort; comorbidity; cost; empowered; immunosenescence; improved; improved outcome; indexing; inhibitor; meetings; phenotyping algorithm; portability; prevent; pulmonary function; respiratory; response; senescence; tool

PROJECT SUMMARY Asthma, the most common chronic disease among children, is one of the five most burdensome diseases in the US. While current care and research efforts focus on symptom control and exacerbation risk, children with asthma may suffer from infectious and inflammatory diseases, ie, asthma-associated infectious and inflammatory disease comorbidities (AIICs) (eg, pneumococcal disease, herpes zoster, appendicitis, and celiac disease). Although AIICs pose serious threats to children with asthma, they are largely under-recognized, as evidenced by diabetes mellitus being widely recognized but a less common chronic illness with a magnitude similar to that for asthma. Presently, the mechanisms underlying AIICs are unknown. We postulate immunosenescence might be related, as AIICs coincide with cardinal immunosenescence features. AIICs are not clinically defined and a suitable tool has not been developed to identify children with AIICs. Thus, no strategies mitigating AIICs risks and outcomes exist. Addressing these knowledge gaps depends upon two key questions: (1) “How can asthmatic children subgroups with increased AIICs risk be identified at a population level using electronic medical records?” and (2) “What immune parameters characterize such children?” Answering these is this proposal's primary goal. To this end, our current R01 study successfully developed, validated, and implemented natural language processing (NLP)- empowered computational phenotyping algorithms for two existing criteria for childhood asthma (Predetermined Asthma Criteria, PAC and Asthma Predictive Index, API). NLP-empowered algorithm application to the 1997-2007 Olmsted County Birth Cohort (OCBC) enabled us to profile a subgroup of children with asthma at increased AIICs risk, disproportionately represented by children who met both NLP-PAC and NLP-API. Our new pilot data suggest asthma potentially accelerates immunosenescence leading to AIICs in a subgroup of asthmatic children. In this renewal proposal, we target this subgroup who meet both NLP-PAC and NLP-API. We will develop and apply NLP-empowered computational phenotyping algorithms for AIICs to identify such children at a population level, then characterize their immune parameters measuring immunosenescence. In Aim 1, we will develop new NLP-empowered computational phenotyping algorithms for recognized and unrecognized AIICs (NLP-AIIC) for children enrolled in Mayo Clinic `s 1997-2016 OCBC, then assess portability of NLP-AIIC at Sanford Children's Hospital, Sioux Falls, SD . In Aim 2, we will identify and characterize children with AIICs through new NLP-AIIC and NLP algorithms for asthma status, by utilizing clinical and immune parameters to measure immunosenescence. In Aim 3, we will assess changes (eg, waning adaptive immunity) over time in immune parameters measuring immunosenescence for 300 children in our R01 study, re-enrolling them for further characterization. This proposed study is indispensable to understanding why some children with asthma develop AIICs, while others do not. This knowledge will allow us to identify, manage, mitigate, and improve outcomes for AIICs among children.

项目总结

项目成果

Analysis of Clinical Variations in Asthma Care Documented in Electronic Health Records Between Staff and Resident Physicians

电子健康记录中工作人员和住院医师之间哮喘护理临床差异的分析

• DOI: 10.3233/978-1-61499-830-3-1170
• 发表时间: 2018
• 期刊: Studies in health technology and informatics
• 作者: S. Sohn;C. Wi;Y. Juhn;Hongfang Liu
• 通讯作者: Hongfang Liu

Identification of asthma control factor in clinical notes using a hybrid deep learning model.

• DOI: 10.1186/s12911-021-01633-4
• 发表时间: 2021-11-09
• 期刊: BMC medical informatics and decision making
• 影响因子: 3.5
• 作者: Agnikula Kshatriya BS;Sagheb E;Wi CI;Yoon J;Seol HY;Juhn Y;Sohn S
• 通讯作者: Sohn S

Rural-urban health disparities for mood disorders and obesity in a midwestern community.

中西部社区中情绪障碍和肥胖的农村健康差异。

• DOI: 10.1017/cts.2020.27
• 发表时间: 2020-03-24
• 期刊: Journal of clinical and translational science
• 影响因子: 2.6
• 作者: Patten CA;Juhn YJ;Ryu E;Wi CI;King KS;Bublitz JT;Pignolo RJ
• 通讯作者: Pignolo RJ

Role of Geographic Risk Factors in COVID-19 Epidemiology: Longitudinal Geospatial Analysis.

• DOI: 10.1016/j.mayocpiqo.2021.06.011
• 发表时间: 2021-10
• 期刊: Mayo Clinic proceedings. Innovations, quality & outcomes
• 作者: Juhn YJ;Wheeler P;Wi CI;Bublitz J;Ryu E;Ristagno EH;Patten C
• 通讯作者: Patten C

Assessing health disparities in children using a modified housing-related socioeconomic status measure: a cross-sectional study.

使用修改后的与住房相关的社会经济地位指标评估儿童的健康差异：一项横断面研究。

• DOI: 10.1136/bmjopen-2016-011564
• 发表时间: 2016
• 期刊: BMJ open
• 影响因子: 2.9
• 作者: Ryu,Euijung;Wi,Chung-Il;Crow,SheriS;Armasu,SebastianM;Wheeler,PhilipH;Sloan,JeffA;Yawn,BarbaraP;Beebe,TimothyJ;Williams,ArthurR;Juhn,YoungJ
• 通讯作者: Juhn,YoungJ