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Kidney disease proteome research

ABSTRACT: The study included 75 participants, among whom 51 patients were diagnosed with kidney diseases: Calculus of kidney (N20.0, URCD) and Cyst of kidney (N28.1, ACDK), Malignant neoplasm of kidney, except renal pelvis (С64, RNCL) and 24 conditionally healthy participants (CNTR).

INSTRUMENT(S): Xevo G2 Q-Tof

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

DISEASE(S): Kidney Cancer

SUBMITTER: Anna Kaysheva

LAB HEAD: Anna Kaysheva

PROVIDER: PXD051799 | Pride | 2025-01-07

REPOSITORIES: pride

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Project description:Rationale There is a need for new and better biomarkers for hypertrophic cardiomyopathy (HCM) which correlate more closely with disease progression as determined by clinical imaging and biohumoral information. We have used a combination of heart tissue and plasma proteomics to identify potential biomarkers for HCM and developed them into an exploratory targeted proteomic assay. Objective To identify informative staging biomarkers for HCM and develop them into a blood test. The test using 10 µl of plasma, was developed into a 10 min liquid chromatography-tandem/mass spectrometry (LC-MS/MS) assay to analyze multiple candidate biomarkers and evaluate their association with clinical phenotypes in patients with HCM. Methods and Results Myocardial tissue and plasma samples from patients with HCM and healthy volunteers (controls) were screened using a combined gel- and nano-LC quadrupole time of flight MS approach. Twenty-six potential biomarkers were identified from the proteomics screens and developed into a multiplexed targeted proteomic assay. Their association with clinical phenotypes was tested in plasma samples collected from 207 prospectively recruited participants: 110 patients with HCM (50.1 ± 15.0 years, 70% male; 48 [44%] with identified genetic mutations) and 97 controls (49.6 ± 13.4 years, 58% male), randomly split into training (80 HCM, 67 controls) and validation datasets (30 HCM, 30 controls). Six markers (Aldolase Fructose-Bisphosphate A, Complement C3, Glutathione S-Transferase Omega 1, Ras Suppressor Protein 1, Talin 1, and Thrombospondin 1) were significantly increased (P<0.006) in the plasma of HCM patients compared to controls in the training dataset. These markers correlated with left ventricular (LV) wall thickness, LV mass and % myocardial scar on cardiovascular magnetic resonance imaging. Using supervized machine learning (ML) this panel differentiated HCM from controls (area under the curve: 0.89 in the training dataset, sensitivity 96%, 95% confidence interval [CI] 77–93; specificity 87%, 95%CI 77–94; and 0.87 in the validation dataset, sensitivity 97%, 95%CI 83–100; specificity 77%, 95%CI 58–90). Four of the biomarkers as well as the composite ML score of the plasma proteome correlated with the presence of nonsustained ventricular tachycardia and the estimated 5-year risk of sudden cardiac death. Conclusion By developing a high-throughput, multiplex, and targeted proteomic plasma assay we identified 6 biomarkers that correlate with the presence of disease and with clinical risk score for sudden cardiac death.

			Action	DRS
	230426_RNCL_S042.mgf	Mgf
	230426_RNCL_S042.raw.zip	Raw
	230426_RNCL_S042_IA_workflow.xml	Xml
	230426_RNCL_S096.mgf	Mgf
	230426_RNCL_S096.raw.zip	Raw

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Kidney disease proteome research

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