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Does Proteomic Mirror Reflect Clinical Characteristics of Obesity?
- Source :
- Journal of Personalized Medicine, Vol 11, Iss 64, p 64 (2021), Journal of Personalized Medicine, Volume 11, Issue 2
- Publication Year :
- 2021
- Publisher :
- MDPI AG, 2021.
-
Abstract
- 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 &ldquo<br />cheap calories&rdquo<br />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.
- Subjects :
- obesity
lcsh:Medicine
Medicine (miscellaneous)
030209 endocrinology & metabolism
Disease
Type 2 diabetes
Bioinformatics
Article
BMI
03 medical and health sciences
proteomics
0302 clinical medicine
Metabolically healthy obesity
medicine
Preventable death
mass spectrometry
030304 developmental biology
0303 health sciences
business.industry
lcsh:R
medicine.disease
Obesity
Chronic disease
Obese subjects
blood tests
business
Subjects
Details
- ISSN :
- 20754426
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- Journal of Personalized Medicine
- Accession number :
- edsair.doi.dedup.....b1d19aca3e0d13ed5eebd6a160ac46c1
- Full Text :
- https://doi.org/10.3390/jpm11020064