Genetic Associations of TCF7L2 (rs7903146) and PPARG (rs1801282) with Prediabetes in the Ethnic Kazakh Population
2024

Genetic Links to Prediabetes in Kazakhs

Sample size: 400 publication 10 minutes Evidence: high

Author Information

Author(s): Azhar Dyussupova, Gulnara Svyatova, Galina Berezina, Altay Dyussupov, Bauyrzhan Omarkulov, Anastassiya Dzharmukhametova, Oxana Yurkovskaya, Venera Akhmetova, Asylzhan Dyussupova

Primary Institution: Semey Medical University

Hypothesis

This study aims to investigate the genetic contribution of polymorphic variants of the TCF7L2 (rs7903146) and PPARG (rs1801282) genes to the risk of developing prediabetes in individuals of Kazakh ethnicity.

Conclusion

The study found that certain genetic variants significantly increase the risk of developing prediabetes in the Kazakh population.

Supporting Evidence

  • Patients with prediabetes had higher birth weight and BMI compared to controls.
  • Carriers of the GG genotype of PPARG had a 9.8 times higher risk of prediabetes.
  • Carriers of the TT genotype of TCF7L2 had a 10.7 times higher risk of prediabetes.
  • Significant differences in allele and genotype frequencies were observed between cases and controls.

Takeaway

This study looked at how certain genes might make Kazakh people more likely to get prediabetes, which is a condition that can lead to diabetes if not caught early.

Methodology

A case-control study involving 200 cases with prediabetes and 200 prediabetes-free controls, using real-time PCR for genotyping.

Potential Biases

Potential selection bias due to the focus on specific regions and ethnic groups.

Limitations

The study's case-control design may limit the generalizability of the findings to the broader population.

Participant Demographics

Participants were ethnic Kazakhs aged 16–60 years.

Statistical Information

P-Value

0.003 for PPARG (rs1801282), p<0.001 for TCF7L2 (rs7903146)

Confidence Interval

95% CI: 2.124–44.922 for PPARG, 95% CI: 1.309–87.939 for TCF7L2

Statistical Significance

p<0.05

Digital Object Identifier (DOI)

10.3390/diagnostics14242769

Want to read the original?

Access the complete publication on the publisher's website

View Original Publication