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Published on: April 26, 2019
[PHENOTYPIC POLYMORPHISM OF N-ACETYLTRANSFERASE 2 IN PATIENTS WITH DIABETES MELLITUS]
I Doroshkevych1, O Yakovleva1, O Kyrychenko1
1National Pirogov Memorial Medical University, Vinnytsia, Ukraine.
N-acetyltransferase 2 (NAT2) activity shows bimodal distribution in healthy individuals and type 2 diabetes patients. This study developed a scale using anthropometric indicators to predict acetylation status without biochemical tests.
Area of Science:
- Pharmacogenetics
- Human genetics
- Metabolic disorders
Background:
- Polymorphism in N-acetyltransferase 2 (NAT2) influences disease risk and drug metabolism.
- Understanding NAT2 activity is crucial for personalized medicine and pharmacogenetics.
Purpose of the Study:
- To investigate the phenotypic polymorphism of NAT2 in healthy subjects and type 2 diabetes mellitus patients.
- To analyze the distribution of genetic determinants related to NAT2 acetylation status.
- To develop a predictive scale for NAT2 acetylation status using anthropometric indicators.
Main Methods:
- Phenotypic analysis of NAT2 activity in 141 healthy subjects and 115 type 2 diabetes patients.
- Genetic analysis correlating acetylation status with anthropometric and phenotypic traits.
- Development of an acetylation phenotype prediction scale based on anthropometric indicators.
Main Results:
- A bimodal distribution of NAT2 phenotypic polymorphism was observed in both diabetic patients and healthy individuals.
- No significant gender differences in NAT2 activity were found in either group.
- Specific anthropometric traits (eye color, dimples, ear lobe size, tongue rolling) and hair color were found to be associated with NAT2 acetylation status in diabetic patients.
Conclusions:
- NAT2 activity exhibits bimodal distribution, suggesting distinct acetylator phenotypes.
- Anthropometric indicators can potentially predict NAT2 acetylation status, offering a non-invasive assessment method.
- These findings may contribute to a better understanding of genotype-phenotype correlations in pharmacogenetics and disease risk.
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