Does Proteomic Mirror Reflect Clinical Characteristics of Obesity?

被引:4
|
作者
Kiseleva, Olga I. [1 ]
Arzumanian, Viktoriia A. [1 ]
Poverennaya, Ekaterina V. [1 ]
Pyatnitskiy, Mikhail A. [1 ]
Ilgisonis, Ekaterina V. [1 ]
Zgoda, Victor G. [1 ]
Plotnikova, Oksana A. [2 ]
Sharafetdinov, Khaider K. [2 ,3 ]
Lisitsa, Andrey V. [1 ]
Tutelyan, Victor A. [2 ,4 ]
Nikityuk, Dmitry B. [2 ,4 ]
Archakov, Alexander I. [1 ]
Ponomarenko, Elena A. [1 ]
机构
[1] Inst Biomed Chem, Pogodinskaya St 10-8, Moscow 119121, Russia
[2] Russian Acad Sci, Fed Res Ctr Nutr Biotechnol & Food Safety, Ustinsky Passage 2-14, Moscow 109240, Russia
[3] Minist Hlth Russian Federat, Russian Med Acad Continuing Profess Educ, Barrikadnaya St 2-1, Moscow 125993, Russia
[4] Sechenov Univ, IM Sechenov First Moscow State Med Univ, Minist Hlth Russian Federat, Trubetskaya St 8-2, Moscow 119991, Russia
来源
JOURNAL OF PERSONALIZED MEDICINE | 2021年 / 11卷 / 02期
关键词
obesity; BMI; blood tests; proteomics; mass spectrometry; BODY-MASS INDEX; HORMONE-BINDING GLOBULIN; APOLIPOPROTEIN C-II; ADIPOSE-TISSUE; WEIGHT-LOSS; METABOLICALLY HEALTHY; APOPTOSIS INHIBITOR; INSULIN-RESISTANCE; GENE; ZINC-ALPHA-2-GLYCOPROTEIN;
D O I
10.3390/jpm11020064
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Obesity is a frightening chronic disease, which has tripled since 1975. It is not expected to slow down staying one of the leading cases of preventable death and resulting in an increased clinical and economic burden. Poor lifestyle choices and excessive intake of "cheap calories" are major contributors to obesity, triggering type 2 diabetes, cardiovascular diseases, and other comorbidities. Understanding the molecular mechanisms responsible for development of obesity is essential as it might result in the introducing of anti-obesity targets and early-stage obesity biomarkers, allowing the distinction between metabolic syndromes. The complex nature of this disease, coupled with the phenomenon of metabolically healthy obesity, inspired us to perform data-centric, hypothesis-generating pilot research, aimed to find correlations between parameters of classic clinical blood tests and proteomic profiles of 104 lean and obese subjects. As the result, we assembled patterns of proteins, which presence or absence allows predicting the weight of the patient fairly well. We believe that such proteomic patterns with high prediction power should facilitate the translation of potential candidates into biomarkers of clinical use for early-stage stratification of obesity therapy.
引用
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页码:1 / 14
页数:14
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