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Sex-Specific Associations Between MTHFR, PPARG and ADRB3 Polymorphisms, Habitual Nutrient Intake and Metabolic Risk
Irina A Lapik1, Inna Yu Tarmaeva1, Dmitry B Nikityuk1,2
1Federal Research Centre of Nutrition, Biotechnology and Food Safety, 2/14 Ustinsky Proyezd, Moscow 109240, Russia.
Nutrients
|August 13, 2026
Summary
Genetic variations influence obesity-related metabolic risks, with specific gene polymorphisms showing sex-specific dietary intake patterns in patients with obesity. These findings suggest tailored, sex-specific dietary interventions may be needed to mitigate health risks.
Area of Science:
- Genetics
- Nutritional Science
- Metabolic Health
Background:
- Genetic polymorphisms are known to influence metabolic complications associated with obesity.
- Understanding how specific genotypes affect dietary intake and sex-based differences is crucial for personalized medicine.
Purpose of the Study:
- To investigate sex-specific associations between common genetic polymorphisms (MTHFR C677T, PPARG Pro12Ala, ADRB3 Trp64Arg) and habitual nutrient intake in obese patients.
- To generate sex-differentiated dietary hypotheses for future research.
Main Methods:
- Cross-sectional study of 348 obese patients (83 men, 265 women) aged 18-60.
- Genotyping via allele-specific real-time PCR; dietary intake assessed using a software-based questionnaire.
- Statistical analysis included Kruskal-Wallis, Mann-Whitney tests with Bonferroni correction, and adjusted regression models.
Main Results:
- Significant genotype-phenotype associations were observed, with sex-specific differences.
- In men, MTHFR C/T was linked to hypercaloric intake and hypertension risk; ADRB3 Trp64Arg to cholesterol overconsumption.
- In women, PPARG G/G was associated with elevated ALT; MTHFR T/T showed links to sugar intake and hypertension tendency.
Conclusions:
- Genetic polymorphisms correlate with sex-specific dietary intake patterns in obesity, extending beyond biochemical risk associations.
- Proposed genotype-informed dietary strategies (e.g., caloric, cholesterol, sugar restriction) require prospective validation.
- Sex-specific, early-life interventions informed by genetic data may optimize metabolic risk reduction.
