Development of a multi-RNA signature in blood towards a rapid diagnostic test to robustly distinguish patients with acute myocardial infarction
Development of a multi-RNA signature in blood towards a rapid diagnostic test to robustly distinguish patients with acute myocardial infarction
批准号:
10603548
负责人:
Timothy E Sweeney
金额:
$29.98万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-07-01 至 2024-06-30
关键词:
Accident and Emergency departmentAcute myocardial infarctionAddressAffectBayesian MethodBiological MarkersBloodBlood specimenChest PainClinicalClinical SensitivityCohort AnalysisCollaborationsDataData SetDevelopmentDiagnosisDiagnosticDiagnostic testsElectrocardiogramEmergency Department patientEmergency department visitEngineeringGene ExpressionGenerationsGenesGeographyGoalsGrantHealth Care CostsHealthcareHeterogeneityImmune responseLettersLibrariesLifeLogistic RegressionsMachine LearningMarketingMeasurementMeasuresMessenger RNAMeta-AnalysisMethodsModelingMyocardial InfarctionOutcomePatient TriagePatient-Focused OutcomesPatientsPerformancePhasePhenotypePopulationPreparationProcessProspective StudiesRNARapid diagnosticsResearchRetrospective cohortSamplingSensitivity and SpecificitySepsisSmall Business Innovation Research GrantSystemTarget PopulationsTestingTimeTrainingTranslatingTriageTroponinValidationWorkacute infectionacute symptomanalysis pipelinebioinformatics pipelineblindclinical diagnosticsclinically actionableclinically relevantcohortcombatdata integrationgenetic signatureheterogenous dataimprovedinstrumentmachine learning classifiermachine learning methodmachine learning modelmachine learning pipelinemolecular diagnosticsmultilayer perceptronperipheral bloodpersonalized diagnosticspoint of carepoint of care testingpoint-of-care diagnosticsproduct developmentprototypereal world applicationresearch clinical testingresponserisk stratificationsuccesssupport vector machinetranscriptome sequencingtranscriptomics
中文摘要
摘要
胸痛是急性心肌梗死(AMI)的主要症状,约占所有急诊的5
部门(艾德)探访。在没有ECG异常的情况下,AMI的诊断金标准依赖于连续的
肌钙蛋白(cTn)测量结果在20 - 40%的患者中不确定,需要额外检测,
在急诊室进行长期观察。如果没有适当的治疗而漏诊AMI,
因此排除诊断需要非常高的灵敏度。因此,快速护理点(POC)测试用作
辅助cTn,提高诊断性能,将是革命性的风险分层和及时,
ED中疑似MI患者的安全分诊。
Inflammatix是一家分子诊断公司,专注于开发并将一流的产品推向市场,
基于免疫反应的数据驱动测试。我们开发了一种即时检测仪器,MyRNA ™,能够
在30分钟内(操作时间<2分钟)直接从患者血液中定量多达64种mRNA,
在完全一次性的盒中。我们专注于使用最先进的多队列分析和机器学习
(ML)识别和验证强大的生物标志物,这些生物标志物在现实世界的数据异质性中普遍存在,
临床背景。先前的工作证明了血液基因表达作为MI生物标志物的潜力,
然而,基于血液基因表达中的免疫应答的临床测试还有待开发。我们应用
我们的分析框架,6公开可用的数据集,并确定了多基因AMI签名在外周血淋巴细胞,
血液,使我们能够区分AMI患者与临床相关的控制AUC~0.95。
在这个项目中,我们建议通过研究和初步的初步结果,
发展阶段,直到正式的临床诊断发展。我们将产生大量的
独立数据,利用Inflammatix ML功能进一步完善mRNA签名,并提供强大的
分类器准备在前瞻性研究中进行验证。在具体目标1中,我们将生成,处理和分析
来自回顾性队列的900份血液样本的RNA-seq数据,接近代表目标测试人群。
在具体目标2中,我们将首先完善,优化和验证mRNA签名;然后开发原型
ML分类器。具体来说,我们将1)整合所有队列的表达数据,同时最大限度地减少偏倚; 2)应用
贝叶斯多队列框架,用于300个新样本的最终基因集选择; 3)开发和评估
AMI分类器原型的区分性能;以及4)在600
看不见的样本这些步骤将产生:i)经验证的AMI基因集; ii)综合数据集;以及iii)
分类器原型(AUC> 0.90),准备通过2期研究中的前瞻性研究进行临床验证。这
当在Inflammatix的POC仪器MyRNA ™上开发一个检测盒时,将有助于临床医生的分类
这将有助于患者对疑似MI的诊断做出更好的决定,改善患者的预后,并降低医疗成本。
英文摘要
ABSTRACT
Chest pain, the main symptom of acute myocardial infarction (AMI), accounts for ~5% of all emergency
department (ED) visits. In the absence of ECG abnormalities, diagnostic gold standard for AMI relies on serial
troponin (cTn) measurements which are inconclusive in 20-40% of patients, requiring additional testing and
prolonged observation in the ED. A missed diagnosis of AMI without proper treatment is life threatening and
thus rule-out diagnosis requires very high sensitivity. Hence, a rapid point of care (POC) test utilized as an
adjunct to cTn with enhanced diagnostic performance would be revolutionary for risk stratification and timely and
safe triaging of patients with suspected MI in ED.
Inflammatix is a molecular diagnostics company focused on developing and bringing to market best in class,
immune response based, data-driven testing. We developed a point-of-care instrument, MyRNA™, capable of
quantitating up to 64 mRNAs in under 30 minutes (with <2 minutes operator time), directly from patients’ blood,
in a fully disposable cartridge. We specialize in use of state-of-art multi-cohort analysis and machine learning
(ML) to identify and validate robust biomarkers that generalize across real-world data heterogeneity, in diverse
clinical contexts. Previous work demonstrated the potential of blood gene expression as a biomarker for MI,
however a clinical test based on immune response in blood gene expression is yet to be developed. We applied
our analytical framework to 6 publicly available datasets and identified a multi-gene AMI signature in peripheral
blood that allows us to differentiate patients with AMI from clinically relevant controls with AUC ~ 0.95.
In this project, we propose to take the AMI signature from preliminary results through research and initial
development stages, up to formal clinical diagnostic development. We will generate a significant amount of
independent data, leverage Inflammatix ML capabilities to further refine the mRNA signature and deliver a robust
classifier ready for validation in prospective studies. In Specific Aim 1, we will generate, process, and analyze
RNA-seq data for 900 blood samples from retrospective cohorts closely representing the target test population.
In Specific Aim 2, we will first refine, optimize, and validate the mRNA signature; and then develop a prototype
ML classifier. Specifically, we will 1) integrate expression data from all cohorts while minimizing bias; 2) apply
Bayesian multi-cohort framework for final gene set selection with 300 new samples; 3) develop and evaluate
discriminatory performance of AMI classifier prototype; and 4) validate the AMI classifier prototype on 600
unseen samples. These steps will produce: i) a validated set of genes for AMI; ii) an integrated dataset; and iii)
a classifier prototype (AUC > 0.90), ready for clinical validation via prospective studies in Phase 2 research. This
test, when developed as a cartridge on Inflammatix’s POC instrument, MyRNA™, will facilitate clinician’s triaging
decisions of patients with suspected MI, improve patient outcomes, and reduce healthcare costs.
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会议论文
Validation and early development of a blood-based rapid diagnostic test for sepsis endotypes
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批准号:10462722
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项目类别:
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资助金额:$101.8万
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财政年份:2021
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负责人:Timothy E Sweeney
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依托单位:
Validation and early development of a blood-based rapid diagnostic test for sepsis endotypes
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批准号:10324978
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项目类别:
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资助金额:$68.39万
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财政年份:2021
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负责人:Timothy E Sweeney
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依托单位:
海外基金