Clinical Informatics to Advance Epidemiology and Pharmacogenetics of Serious Cutaneous Adverse Drug Reactions
Clinical Informatics to Advance Epidemiology and Pharmacogenetics of Serious Cutaneous Adverse Drug Reactions
批准号:
10470022
负责人:
Li Zhou
金额:
$70.25万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-16 至 2024-08-31
关键词:
AddressAdherenceAdverse eventAdverse reactionsAffectAfrican AmericanAllelesAllergic ReactionAllopurinolAntibioticsAutoimmuneAutoimmune DiseasesBiological MarkersCarbamazepineCase-Control StudiesCessation of lifeClinicalClinical DataClinical InformaticsClinical SciencesCodeCountryCutaneousDataDermatologyDevelopmentDiagnosticDiseaseDrug Administration RoutesDrug ExposureDrug PrescriptionsDrug usageEarly DiagnosisElectronic Health RecordEosinophiliaEpidemiologyEthnic groupFemaleFutureGeneticGenetic RiskGenetic TranslationGenomicsGoalsHLA AntigensHealthcareHealthcare SystemsHistocompatibility Antigens Class IHypersensitivityIatrogenesisImmunologicsImmunologyInfectionInformaticsInpatientsInstitutionInternationalKnowledgeLeadMachine LearningMandatory ReportingMedical GeneticsMethodologyMethodsMinority GroupsMissionModelingMonobactamsMorbidity - disease rateNatural Language ProcessingNevirapineOutpatientsPatientsPharmaceutical PreparationsPharmacogeneticsPharmacologyPhenotypePopulation HeterogeneityPrevalencePreventionProcessQuality of lifeRaceReactionRegistriesReportingReproducibilityResearchRiskRisk FactorsScienceSourceSpecificityStandardizationStevens-Johnson SyndromeSulfonamidesSurveysSymptomsSyndromeSystemTechniquesTechnologyTextToxic Epidermal NecrolysisTranslatingTranslationsUnited StatesUnited States Food and Drug AdministrationUnited States National Institutes of HealthUniversitiesValidationVancomycinVariantabacaviradverse drug reactionantimicrobialbasebeta-Lactamscare burdencase controlcase findingclinical decision-makingclinical phenotypeclinical practiceclinical riskclinically relevantcohortcomorbiditydata repositorydata sharingdesigndisabilitydosagegenetic associationgenetic risk factorhealth disparity populationsimmunoreactionimprovedmedication compliancemedication safetyminority health disparitymortalitypatient populationpatient registrypreventracial and ethnicrisk stratificationscreeningsexsharing platformsoutheast Asiantargeted treatment
中文摘要
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英文摘要
Project Summary
Severe cutaneous adverse reactions (SCARs) are morbid immunologic reactions to drugs that confer a
mortality of 10-50%. Over the last decade, significant promise for prediction and prevention has come from the
discovery that many SCARs are associated with variation within HLA class I alleles. For HLA-B*15:02, this has
led to routine pre-prescription screening for carbamazepine in many Southeast Asian countries and a significant
reduction in cases of carbamazepine SJS/TEN. Despite this progress, there is little known about genetic and
epidemiological risk factors for SCARs related to commonly used drugs such as antibiotics. There is also limited
information about HLA risk for SCARs across the diverse populations present in the United States. Furthermore,
imprecision of clinical phenotyping and lack of standardized coding has led to challenges in finding SCAR cases
in the electronic health record (EHR). Our proposed study aims to address critical challenges and gaps in our
knowledge of antibiotic SCARs.
In Aim 1, we will leverage advanced informatics and longitudinal EHR data for over 11 million patients from
Partners HealthCare System since the 1980s to identify SCAR cases. We will create, optimize and standardize
reproducible methods for finding SCAR cases and validating a cohort of SCAR patients. This iterative process
will be used to refine and disseminate an electronic phenotype to be validated cross-institutionally.
In Aim 2, we will analyze SCAR prevalence and conduct a case-control study to identify drug-specific and
patient-specific risk factors for antibiotic-associated SCARs. We will compare clinical sequelae, quality of life and
adherence of SCAR patients compared to controls through validated survey instruments.
In Aim 3, we will identify candidate HLA and genetic associations from patients with validated antibiotic-
associated SCARs. We will examine difference in genetic risk in minority and health disparity populations and
predict that we will be powered to establish HLA associations for vancomycin DRESS (i.e., drug reaction with
eosinophilia and systemic symptoms) and sulfonamide antimicrobial and beta-lactam SCAR. HLA alone, or
in combination with clinical risk factors, can lead to improved SCAR prevention and early diagnosis. We will
establish a data sharing platform, in the form of an online electronic phenotype and patient registry, that can be
used to enlarge SCAR cohorts for future large-scale genomics studies.
The roadmap we develop will translate into the development of electronic phenotypes for serious adverse
drug reactions that facilitate genetic discovery. Knowledge gained will be crucial to the translation of genetic data
into clinical decision making. This is in close alignment with NIH’s research mission to accelerate genetic
discovery for iatrogenic and preventable drug-induced diseases that will translate into prevention, earlier
diagnosis and an enhanced mechanistic understanding that may lead to targeted therapeutic approaches.
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DOI:
10.1016/j.jaip.2023.06.010
发表时间:
2023-12-06
期刊:
JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY-IN PRACTICE
影响因子:
9.4
作者:
[Blumenthal,Kimberly G., Bansal,Priya, Pappalardo,Andrea A.]
通讯作者:
Pappalardo,Andrea A.
Drug reaction with eosinophilia and systemic symptoms: Medication adherence and quality of life in survivors.
伴有嗜酸性粒细胞增多和全身症状的药物反应:幸存者的用药依从性和生活质量。
DOI:
10.1016/j.jaip.2023.10.022
发表时间:
2024
期刊:
The journal of allergy and clinical immunology. In practice
影响因子:
--
作者:
[Jaggers,Jordon, Samarakoon,Upeka, King,Andrew, Kroshinsky,Daniela, Bassir,Fatima, Salem,Abigail, Phillips,Elizabeth, Wang,Liqin, Zhou,Li, Blumenthal,KimberlyG]
通讯作者:
Blumenthal,KimberlyG
A deep learning approach for transgender and gender diverse patient identification in electronic health records.
电子健康记录中跨性别和性别多样化患者识别的深度学习方法。
DOI:
10.1016/j.jbi.2023.104507
发表时间:
2023
期刊:
Journal of biomedical informatics
影响因子:
4.5
作者:
[Hua,Yining, Wang,Liqin, Nguyen,Vi, Rieu-Werden,Meghan, McDowell,Alex, Bates,DavidW, Foer,Dinah, Zhou,Li]
通讯作者:
Zhou,Li
Deep learning for detection of drug hypersensitivity reactions.
用于检测药物超敏反应的深度学习。
DOI:
10.1016/j.jaci.2023.03.004
发表时间:
2023
期刊:
The Journal of allergy and clinical immunology
影响因子:
--
作者:
[Blackley,SuzanneV, Salem,Abigail, Zhou,Li]
通讯作者:
Zhou,Li
Drug reaction eosinophilia and systemic symptoms: Clinical phenotypic patterns according to causative drug.
药物反应嗜酸性粒细胞增多和全身症状:根据致病药物的临床表型模式。
DOI:
10.1016/j.jaad.2023.05.067
发表时间:
2023
期刊:
Journal of the American Academy of Dermatology
影响因子:
13.8
作者:
[Blumenthal,KimberlyG, Alvarez-Arango,Santiago, Kroshinsky,Daniela, Lo,Ying-Chih, Samarakoon,Upeka, Salem,AbigailRose, Fu,Xiaoqing, Bassir,Fatima, Wang,Liqin, Jaggers,Jordon, Phillips,Elizabeth, Zhou,Li]
通讯作者:
Zhou,Li
Clinical Informatics to Advance Epidemiology and Pharmacogenetics of Serious Cutaneous Adverse Drug Reactions
-
批准号:10228607
-
项目类别:
-
资助金额:$69.75万
-
财政年份:2019
-
负责人:Li Zhou
-
依托单位:
Clinical Informatics to Advance Epidemiology and Pharmacogenetics of Serious Cutaneous Adverse Drug Reactions
-
批准号:10018800
-
项目类别:
-
资助金额:$69.62万
-
财政年份:2019
-
负责人:Li Zhou
-
依托单位:
MicroRNAs regulate skin Langerhans cells
-
批准号:10250383
-
项目类别:
-
资助金额:$32.12万
-
财政年份:2018
-
负责人:Li Zhou
-
依托单位:
Improving Allergy Documentation and Clinical Decision Support in the EHR
-
批准号:9915842
-
项目类别:
-
资助金额:$39.41万
-
财政年份:2018
-
负责人:Li Zhou
-
依托单位:
MicroRNAs regulate skin Langerhans cells
-
批准号:10006075
-
项目类别:
-
资助金额:$33.11万
-
财政年份:2018
-
负责人:Li Zhou
-
依托单位:
Encoding and Processing Patient Allergy Information in EHRs
-
批准号:8642929
-
项目类别:
-
资助金额:$48.99万
-
财政年份:2013
-
负责人:Li Zhou
-
依托单位:
Encoding and Processing Patient Allergy Information in EHRs
-
批准号:8741955
-
项目类别:
-
资助金额:$48.99万
-
财政年份:2013
-
负责人:Li Zhou
-
依托单位:
Integration of an NLP-based application to support medication management
-
批准号:8496045
-
项目类别:
-
资助金额:$14.82万
-
财政年份:2012
-
负责人:Li Zhou
-
依托单位:
Integration of an NLP-based application to support medication management
-
批准号:8354008
-
项目类别:
-
资助金额:$14.93万
-
财政年份:2012
-
负责人:Li Zhou
-
依托单位:
Improving Outpatient Medication Lists Using Temporal Reasoning and Clinical Texts
-
批准号:7774682
-
项目类别:
-
资助金额:$4.88万
-
财政年份:2009
-
负责人:Li Zhou
-
依托单位:
Improving Outpatient Medication Lists Using Temporal Reasoning and Clinical Texts
-
批准号:7935475
-
项目类别:
-
资助金额:$5.01万
-
财政年份:2009
-
负责人:Li Zhou
-
依托单位:
海外基金