| Literature DB >> 33090017 |
Alina Golea-Secara1,2, Cristian Munteanu3, Mirela Sarbu4, Octavian M Cretu2,5, Silvia Velciov1,2, Adrian Vlad2,6, Flaviu Bob1,2, Florica Gadalean1,2, Cristina Gluhovschi2, Oana Milas1,2, Anca Simulescu1,2, Maria Mogos-Stefan1,2, Mihaela Patruica1,2, Ligia Petrica1,2,7, Alina D Zamfir4.
Abstract
Aim: An advanced proteomics platform for protein biomarker discovery in diabetic chronic kidney disease (DKD) was developed, validated and implemented. Materials & methods: Three Type 2 diabetes mellitus patients and three control subjects were enrolled. Urinary peptides were extracted, samples were analyzed on a hybrid LTQ-Orbitrap Velos Pro instrument. Raw data were searched using the SEQUEST algorithm and integrated into Proteome Discoverer platform. Results & discussion: Unique peptide sequences, resulted sequence coverage, scoring of peptide spectrum matches were reported to albuminuria and databases. Five proteins that can be associated with early DKD were found: apolipoprotein AI, neutrophil gelatinase-associated lipocalin, cytidine deaminase, S100-A8 and hemoglobin subunit delta.Entities:
Keywords: albuminuria; diabetes mellitus Type 2; inflammation; proximal tubule dysfunction; urinary proteomics
Year: 2020 PMID: 33090017 DOI: 10.2217/bmm-2020-0308
Source DB: PubMed Journal: Biomark Med ISSN: 1752-0363 Impact factor: 2.851