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Cardiovascular Research 2019-Aug

A Plasma Proteogenomic Signature for Fibromuscular Dysplasia.

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Il collegamento viene salvato negli appunti
Jeffrey Olin
Antonio Di Narzo
Valentina d'Escamard
Daniella Kadian-Dodov
Haoxiang Cheng
Adrien Georges
Annette King
Allison Thomas
Temo Barwari
Katherine Michelis

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Fibromuscular dysplasia (FMD) is a poorly understood disease that predominantly affects women during middle-life, with features that include stenosis, aneurysm and dissection of medium-large arteries. Recently, plasma proteomics has emerged as an important means to understand cardiovascular diseases. Our objectives were: (1) To characterize plasma proteins and determine if any exhibit differential abundance in FMD subjects versus matched healthy controls; (2) To leverage these protein data to conduct systems analyses to provide biologic insights on FMD, and explore if this could be developed into a blood-based FMD test.Females with 'multifocal' FMD and matched healthy controls underwent clinical phenotyping, dermal biopsy and blood draw. Using dual-capture proximity-extension-assay and nuclear magnetic resonance-spectroscopy, we evaluated plasma levels of 981 proteins and 31 lipid sub-classes, respectively. In a discovery cohort (Ncases=90, Ncontrols=100), we identified 105 proteins and 16 lipid sub-classes (predominantly triglycerides and fatty acids) with differential plasma abundance in FMD cases versus controls. In an independent cohort (Ncases=23, Ncontrols=28), we successfully validated 37 plasma proteins and 10 lipid sub-classes with differential abundance. Among these, 5/37 proteins exhibited genetic control and Bayesian analyses identified 3 of these as potential upstream drivers of FMD. In a third cohort (Ncases=506, Ncontrols=876) the genetic locus of one of these upstream disease drivers, CD2-associated protein (CD2AP), was independently validated as being associated with risk of having FMD (OR = 1.36; P = 0.0003). Immune-fluorescence staining identified that CD2AP is expressed by the endothelium of medium-large arteries. Finally, machine learning trained on the discovery cohort was used to develop a test for FMD. When independently applied to the validation cohort, the test showed a c-statistic of 0.73 and sensitivity of 78.3%.FMD exhibits a plasma proteogenomic and lipid signature that includes potential causative disease drivers, and which holds promise for developing a blood-based test for this disease.Fibromuscular dysplasia (FMD) is a poorly understood disease with no specific therapies, which can cause stenosis, aneurysm and dissection of medium-large arteries. At present, FMD is usually diagnosed by imaging studies, and screening for this disease can be challenging. We performed a 'reverse-translational' clinical study leveraging plasma and DNA samples from FMD patients and healthy matched controls to better understand this disease. We found that FMD patients exhibit a plasma proteogenomic signature that includes promising disease candidates. While further development will be required, our proof-of-concept analyses suggest that it may also be possible to develop a blood-based test for FMD.

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