Development of a Precision Medicine-based Diagnostic Tool for Membranous Nephropathy

膜性肾病精准医学诊断工具的开发

• 批准号: 10602134
• 负责人: Christopher P Larsen
• 金额: $ 101.85万
• 依托单位: NEPHROPATHOLOGY ASSOCIATES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10602134
• 关键词: Agreement; Antigens; Arkansas; Artificial Intelligence; Autoantibodies; Autoantigens; Autoimmune Diseases; Benchmarking; Biological Assay; Biopsy; Blinded; CLIA certified; Chronic Inflammatory Demyelinating Polyneuropathy; Classification; Clinical; Collaborations; Comparative Study; Core Biopsy; Cost Sharing; Data; Data Analyses; Development; Diagnosis; Disease; Disease Progression; Disease remission; Ensure; Equipment; Etiology; Exclusion; Frozen Sections; Generations; Goals; Human; Individual; Investigation; Kidney Failure; Laboratories; Lead; Life; Link; Malignant Neoplasms; Mass Spectrum Analysis; Medical; Membranous Glomerulonephritis; Methods; Modality; Molecular; Monitor; Nephrotic Syndrome; Outcome; Patients; Performance; Periodicity; Phase; Phospholipase A2; Price; Process; Prognosis; Proteins; Proteomics; Protocols documentation; Publications; Quality Control; Reagent; Resources; Running; Sampling; Science; Serology; Serology test; Services; Severities; Standardization; System; Systemic Lupus Erythematosus; Testing; Thrombospondins; Time; Tissues; Training; Translating; Universities; Validation; base; biobank; clinical practice; commercialization; comorbidity; cost; diagnostic tool; experimental study; follow-up; improved; instrument; instrumentation; kidney biopsy; novel; novel strategies; personalized medicine; phase 1 study; phase 1 testing; precision medicine; programs; receptor; statistical and machine learning; success; tool; trend; validation studies

Project Summary The goal of this program is to initiate commercialization of a mass spectrometry (MS)-based workflow for the diagnosis and classification of membranous nephropathy (MN), a leading cause of nephrotic syndrome, leading to kidney failure in a third of patients. Since the 1950’s, most forms of MN were considered idiopathic in origin, however, based on numerous publications in recent years, it is now broadly accepted that MN is caused by autoantibodies against approximately 20 different endogenous human proteins. The most common MN autoantigen is the phospholipase A2 receptor (PLA2R), and serological analysis of autoantibody titers against this protein has proven to be an indispensable serological tool for monitoring disease progression, severity, and remission (1-3). Arkana and others have identified additional novel autoantigens in MN cases (4-9), and given the success of PLA2R serological testing for personalized treatment, the characterization and clinical validation of the remaining MN autoantigens is urgently required. Furthermore, follow-up investigation of patients positive for these newly identified autoantigens have been linked to life-threatening comorbidities including cancer and specific autoimmune diseases. Because classifying patients based on MN autoantigen may reveal severe underlying conditions, and PLA2R serology will identify only 70% of primary cases, Arkana has partnered with proteomics experts at the University of Arkansas for Medical Sciences (UAMS) to develop an unbiased, MS- based approach to classifying MN of all antigen types. Phase I studies evaluated nearly 300 tissue biopsies from MN patients with previously determined autoantigens including PLA2R, thrombospondin type-1 domain containing 7A (THSD7A) (10), and exostosin1/2 (EXT1/2) (11), with triple negative cases also included. After evaluating a range of computational, statistical, and artificial intelligence data analysis modalities, ranked Z- scores were found to be an effective metric for autoantigen classification, correctly classifying over 95% of samples. During the proposed Phase II program, Arkana will continue collaborating with UAMS to translate this powerful method to clinical practice and commercial availability. Quality control metrics will be developed for the inclusion/exclusion of incoming samples, to ensure the reliability and repeatability of MS analysis and support verification of autoantigen classifications. The analytical pipeline will also be broadened to accommodate additional autoantigen targets, many of which were identified by Arkana’s recent MS analysis of hundreds of biobanked MN samples. Finally, the method will be transferred to Arkana’s CLIA laboratory and validated in a comparative study with UAMS comprising approximately 300 blinded samples representing the full breadth of MN autoantigen classes. Launching this workflow as a commercially available service will not only offer clinicians unprecedented detail for the diagnosis and treatment of MN patients, but also reveal potentially life-threatening comorbidities undetectable by prior generation strategies.

项目总结