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.

IF 2.1 4区生物学 Q3 BIOCHEMICAL RESEARCH METHODS

PROTEOMICS – Clinical Applications Pub Date : 2024-11-01 Epub Date: 2024-07-28 DOI:10.1002/prca.202300238

Carlos Vinicius Ferreira da Silva, Carlos José Ferreira da Silva, Youssef Bacila Sade, Sandra Mara Naressi Scapin, Fabiano L Thompson, Cristiane Thompson, Carina Maciel da Silva-Boghossian, Eidy de Oliveira Santos

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引用次数: 0

Abstract

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.

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探究巴西人口唾液和血浆中与高体重指数 (BMI)、代谢综合征和 2 型糖尿病有关的特定蛋白质模式。

目的：肥胖及其相关代谢紊乱（如 T2DM 和 MeS）是全球日益严重的公共健康问题。我们的目标是在巴西人群中确定具有较高体重指数、MeS 和 T2DM 独有特征的蛋白质模式：实验设计：我们对巴西里约热内卢州的混血人群的唾液和血浆蛋白质组、临床参数进行了分析。志愿者按体重指数分为正常（29 人）、超重（25 人）和肥胖（15 人），并与 MeS（23 人）和 T2DM（11 人）患者进行比较：随机森林（RF）预测模型显示，BMI、HOMA-IR和空腹血糖这三个临床变量对预测MeS和T2DM最为重要。共有六种血浆蛋白（ABCD4、LDB1、PDZ、podoplanin、lipirin-alpha-3 和 WRS）和六种唾液蛋白（血红蛋白亚基 beta、POTEE、T 细胞受体 alpha 可变 9-2、乳转铁蛋白、胱抑素-S、碳酸酐酶 6）在 T2DM 和 MeS 中增强：我们的数据显示，体重异常增加、T2DM 和 MeS 患者的蛋白质组成发生了类似的改变。这一发现证实了所研究人群中这些疾病在分子水平上的密切联系，有可能加深我们对这些疾病的了解，并为开发新型诊断工具铺平道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

PROTEOMICS – Clinical Applications 医学-生化研究方法

CiteScore

5.20

自引率

5.00%

发文量

审稿时长

1 months

期刊介绍： PROTEOMICS - Clinical Applications has developed into a key source of information in the field of applying proteomics to the study of human disease and translation to the clinic. With 12 issues per year, the journal will publish papers in all relevant areas including: -basic proteomic research designed to further understand the molecular mechanisms underlying dysfunction in human disease -the results of proteomic studies dedicated to the discovery and validation of diagnostic and prognostic disease biomarkers -the use of proteomics for the discovery of novel drug targets -the application of proteomics in the drug development pipeline -the use of proteomics as a component of clinical trials.