Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype
Abstract Background The growth in obesity and rates of abdominal obesity in developing countries is due to the dietary transition, meaning a shift from traditional, fiber-rich diets to Westernized diets high in processed foods, sugars, and unhealthy fats. Environmental changes, such as improving the...
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2025-01-01
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| Online Access: | https://doi.org/10.1186/s12920-024-02066-4 |
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| author | Niloufar Rasaei Seyedeh Fatemeh Fatemi Fatemeh Gholami Mahsa Samadi Mohammad Keshavarz Mohammadian Elnaz Daneshzad Khadijeh Mirzaei |
| author_facet | Niloufar Rasaei Seyedeh Fatemeh Fatemi Fatemeh Gholami Mahsa Samadi Mohammad Keshavarz Mohammadian Elnaz Daneshzad Khadijeh Mirzaei |
| author_sort | Niloufar Rasaei |
| collection | DOAJ |
| description | Abstract Background The growth in obesity and rates of abdominal obesity in developing countries is due to the dietary transition, meaning a shift from traditional, fiber-rich diets to Westernized diets high in processed foods, sugars, and unhealthy fats. Environmental changes, such as improving the quality of dietary fat consumed, may be useful in preventing or mitigating the obesity or unhealthy obesity phenotype in individuals with a genetic predisposition, although this has not yet been confirmed. Therefore, in this study, we investigated how dietary fat quality indices with metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO) based on the Karelis criterion interact with genetic susceptibility in Iranian female adults. Methods In the current cross-sectional study, 279 women with overweight or obesity participated. Dietary intake was assessed using a 147-item food frequency questionnaire and dietary fat quality was assessed using the cholesterol-saturated fat index (CSI) and the ratio of omega-6/omega-3 (N6/N3) essential fatty acids. Three single nucleotide polymorphisms-MC4R (rs17782313), CAV-1 (rs3807992), and Cry-1(rs2287161) were genotyped by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique and were combined to produce the genetic risk score (GRS). Body composition was evaluated using a multi-frequency bioelectrical impedance analyzer. Participants were divided into MHO or MUO phenotypes after the metabolic risk assessment based on the Karelis criteria. Results We found significant interactions between GRS and N6/N3 in the adjusted model controlling for confounding factors (age, body mass index, energy, and physical activity) (β = 2.26, 95% CI: 0.008 to 4.52, P = 0.049). In addition, we discovered marginally significant interactions between GRS and N6/N3 in crude (β = 1.92, 95% CI: -0.06 to 3.91, P = 0.058) and adjusted (age and energy) (β = 2.00, 95% CI: -0.05 to 4.05, P = 0.057) models on the MUH obesity phenotype. However, no significant interactions between GRS and CSI were shown in both crude and adjusted models. Conclusion This study highlights the importance of personalized nutrition and recommends further study of widely varying fat intake based on the findings on gene-N6/N3 PUFA interactions. |
| format | Article |
| id | doaj-art-aee1eb0213d44f2a88cfcf84a0fd6f0f |
| institution | Kabale University |
| issn | 1755-8794 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Genomics |
| spelling | doaj-art-aee1eb0213d44f2a88cfcf84a0fd6f0f2025-01-26T12:56:55ZengBMCBMC Medical Genomics1755-87942025-01-0118111210.1186/s12920-024-02066-4Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotypeNiloufar Rasaei0Seyedeh Fatemeh Fatemi1Fatemeh Gholami2Mahsa Samadi3Mohammad Keshavarz Mohammadian4Elnaz Daneshzad5Khadijeh Mirzaei6Micronutrient Research Center, Research Institute for Endocrine Disorders, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical SciencesDepartment of Community Nutrition, School of Nutritional Sciences and Dietetics, Mashhad University of Medical ScienceDepartment of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS)Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS)Department of Nutrition, Science and Research Branch, Islamic Azad UniversityNon-Communicable Diseases Research Center, Alborz University of Medical SciencesDepartment of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS)Abstract Background The growth in obesity and rates of abdominal obesity in developing countries is due to the dietary transition, meaning a shift from traditional, fiber-rich diets to Westernized diets high in processed foods, sugars, and unhealthy fats. Environmental changes, such as improving the quality of dietary fat consumed, may be useful in preventing or mitigating the obesity or unhealthy obesity phenotype in individuals with a genetic predisposition, although this has not yet been confirmed. Therefore, in this study, we investigated how dietary fat quality indices with metabolically healthy obesity (MHO) or metabolically unhealthy obesity (MUO) based on the Karelis criterion interact with genetic susceptibility in Iranian female adults. Methods In the current cross-sectional study, 279 women with overweight or obesity participated. Dietary intake was assessed using a 147-item food frequency questionnaire and dietary fat quality was assessed using the cholesterol-saturated fat index (CSI) and the ratio of omega-6/omega-3 (N6/N3) essential fatty acids. Three single nucleotide polymorphisms-MC4R (rs17782313), CAV-1 (rs3807992), and Cry-1(rs2287161) were genotyped by the polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique and were combined to produce the genetic risk score (GRS). Body composition was evaluated using a multi-frequency bioelectrical impedance analyzer. Participants were divided into MHO or MUO phenotypes after the metabolic risk assessment based on the Karelis criteria. Results We found significant interactions between GRS and N6/N3 in the adjusted model controlling for confounding factors (age, body mass index, energy, and physical activity) (β = 2.26, 95% CI: 0.008 to 4.52, P = 0.049). In addition, we discovered marginally significant interactions between GRS and N6/N3 in crude (β = 1.92, 95% CI: -0.06 to 3.91, P = 0.058) and adjusted (age and energy) (β = 2.00, 95% CI: -0.05 to 4.05, P = 0.057) models on the MUH obesity phenotype. However, no significant interactions between GRS and CSI were shown in both crude and adjusted models. Conclusion This study highlights the importance of personalized nutrition and recommends further study of widely varying fat intake based on the findings on gene-N6/N3 PUFA interactions.https://doi.org/10.1186/s12920-024-02066-4Genetic risk scoreObesityGene-by- environment interactionLipids |
| spellingShingle | Niloufar Rasaei Seyedeh Fatemeh Fatemi Fatemeh Gholami Mahsa Samadi Mohammad Keshavarz Mohammadian Elnaz Daneshzad Khadijeh Mirzaei Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype BMC Medical Genomics Genetic risk score Obesity Gene-by- environment interaction Lipids |
| title | Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype |
| title_full | Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype |
| title_fullStr | Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype |
| title_full_unstemmed | Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype |
| title_short | Interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype |
| title_sort | interaction of genetics risk score and fatty acids quality indices on healthy and unhealthy obesity phenotype |
| topic | Genetic risk score Obesity Gene-by- environment interaction Lipids |
| url | https://doi.org/10.1186/s12920-024-02066-4 |
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