Prospecting Specific Protein Patterns for High Body Mass Index (BMI), Metabolic Syndrome and Type 2 Diabetes in Saliva and Blood Plasma From a Brazilian Population.

Autor: Ferreira da Silva CV; Instituto de Biologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil., da Silva CJF; Faculdade de Ciências Biológicas e Saúde, Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, Brazil.; Programa da Pós-graduação em Biomedicina Translacional, Universidade do Grande Rio -Unigranrio, Duque de Caxias, Brazil., Bacila Sade Y; Programa da Pós-graduação em Biomedicina Translacional, Universidade do Grande Rio -Unigranrio, Duque de Caxias, Brazil., Naressi Scapin SM; Instituto Nacional de Metrologia, Qualidade e Tecnologia (INMETRO), Duque de Caxias, Brazil., Thompson FL; Instituto de Biologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil., Thompson C; Instituto de Biologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil., da Silva-Boghossian CM; Instituto de Biologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil., de Oliveira Santos E; Faculdade de Ciências Biológicas e Saúde, Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro, Brazil.; Programa da Pós-graduação em Biomedicina Translacional, Universidade do Grande Rio -Unigranrio, Duque de Caxias, Brazil.
Jazyk: angličtina
Zdroj: Proteomics. Clinical applications [Proteomics Clin Appl] 2024 Jul 28, pp. e202300238. Date of Electronic Publication: 2024 Jul 28.
DOI: 10.1002/prca.202300238
Abstrakt: Purpose: Obesity and its associated metabolic disorders, such as T2DM and MeS, are a growing public health problem worldwide. Our goal was the identification of protein patterns that are uniquely characteristic of higher BMI, MeS, and T2DM in a Brazilian population.
Experimental Design: Saliva and plasma proteomes, clinical parameters were analyzed in a population from the state of Rio de Janeiro, Brazil, a mixed-race population. Volunteers were sorted by their BMI into normal (n = 29), overweight (n = 25), and obese (n = 15) and were compared with individuals with MeS (n = 23) and T2DM (n = 11).
Results: The Random Forest (RF) predictive model revealed that three clinical variables, BMI, HOMA-IR, and fasting blood glucose, are most important for predicting MeS and T2DM. A total of six plasmatic proteins (ABCD4, LDB1, PDZ, podoplanin, lipirin-alpha-3, and WRS) and six salivary proteins (hemoglobin subunit beta, POTEE, T cell receptor alpha variable 9-2, lactotransferrin, cystatin-S, carbonic anhydrase 6), are enhanced in T2DM and in MeS.
Conclusions and Clinical Relevance: Our data revealed similar alterations in protein composition across individuals with abnormal weight gain, T2DM, and MeS. This finding confirms the close link between these conditions at the molecular level in the studied population, potentially enhancing our understanding of these diseases and paving the way for the development of novel diagnostic tools.
(© 2024 Wiley‐VCH GmbH.)
Databáze: MEDLINE
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