MALDI-TOF MS Characterisation of the Serum Proteomic Profile in Insulin-Resistant Normal-Weight Individuals
Autor: | Eliza Matuszewska, Paweł Bogdański, Dagmara Pietkiewicz, Jan Matysiak, Katarzyna Pastusiak |
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Rok vydání: | 2021 |
Předmět: |
Adult
Male Proteomics Proteome medicine.medical_treatment Serum albumin Ideal Body Weight Article Young Adult Insulin resistance Serotransferrin Diabetes mellitus insulin resistance Medicine Humans TX341-641 protein-peptide profiling MALDI Fibrinogen alpha chain Aged normal-weight obesity Nutrition and Dietetics Proteomic Profile biology Nutrition. Foods and food supply business.industry Insulin Blood Proteins Middle Aged medicine.disease Biochemistry Spectrometry Mass Matrix-Assisted Laser Desorption-Ionization biology.protein Female business Peptides Biomarkers Food Science |
Zdroj: | Nutrients Volume 13 Issue 11 Nutrients, Vol 13, Iss 3853, p 3853 (2021) |
ISSN: | 2072-6643 |
Popis: | Insulin resistance (IR) is one of the most common metabolic disorders worldwide and is involved in the development of diseases, such as diabetes and cardiovascular diseases, affecting civilisations. The possibility of understanding the molecular mechanism and searching for new biomarkers useful in assessing IR can be achieved through modern research techniques such as proteomics. This study assessed the protein–peptide profile among normal-weight patients with IR to understand the mechanisms and to define new risk biomarkers. The research involved 21 IR and 43 healthy, normal-weight individuals, aged 19–65. Serum proteomic patterns were obtained using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry. The proposed methodology identified six proteins differentiating normal weight IR and insulin sensitive individuals. They were fibrinogen alpha chain, serum albumin, kininogen-1, complement C3, serotransferrin, and Ig gamma-1 chain, which could potentially be related to inflammation. However, further investigation is required to confirm their correlation with IR. |
Databáze: | OpenAIRE |
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