Nut consumption, linoleic and α-linolenic acid intakes, and genetics: how fatty acid desaturase 1 impacts plasma fatty acids and type 2 diabetes risk in EPIC-InterAct and PREDIMED studies.

Marcela Guevara, María Dolores Chirlaque López, Chloé Marques, Daniel B Ibsen, Dagfinn Aune, Dolores Corella, Nita G Forouhi, Claudia Agnoli, Matthias B Schulze, Verena Katzke, Anne Tjønneland, Olga Kuxhaus, Susanne Jäger, Inge Huybrechts, Marcela Prada, Alberto Catalano, Tammy Y N Tong, Nicholas J Wareham, Maria-Jose Sánchez, Cristina Razquin, Marta Farràs, Benedetta Bendinelli, Miguel A Martinez-Gonzalez, Stephen J Sharp, Claire Cadeau, Christina C Dahm, Jytte Halkjær, Xuan Ren

Journal: BMC medicine 2025;23(1):344

PMID: 40484934

Plain Language Summary

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Type 2 diabetes is a growing global health concern. Diet, especially the types of fats people eat, may influence the risk of developing the disease. Nuts are rich in healthy unsaturated fats, including linoleic acid and α-linolenic acid, which may help protect against diabetes. However, people process dietary fats differently, partly due to genetic differences. This study was conducted to better understand how diet and genetics interact to influence fatty acid levels in the blood and the risk of type 2 diabetes.

The research analysed data from two large studies: EPIC-InterAct, a European cohort study investigating diet and diabetes risk, and PREDIMED, a Mediterranean diet intervention study. The aim was to examine whether nut consumption and intake of specific fatty acids were associated with blood fatty acid levels and type 2 diabetes risk, and whether genetic variation in the fatty acid desaturase 1 (FADS1) gene influenced these relationships.

The results showed that higher levels of linoleic acid in the blood were associated with a lower risk of developing type 2 diabetes. Nut consumption contributed to higher levels of beneficial unsaturated fatty acids. The study also found that genetic variations in the FADS1 gene influenced how the body processes fatty acids, affecting the levels of certain fatty acids in the blood. This suggests that genetic differences may partly explain why individuals respond differently to dietary fats.

In conclusion, both diet and genetics play important roles in fatty acid metabolism and diabetes risk. Healthcare professionals may use this information to better understand how individual genetic differences can influence the health effects of dietary fats, supporting more personalised nutrition approaches for preventing type 2 diabetes.

Abstract

BACKGROUND

Dietary guidelines recommend replacing saturated fatty acid with unsaturated fats, particularly polyunsaturated fatty acids. Cohort studies do not suggest a clear benefit of higher intake of polyunsaturated fatty acids but, in contrast, higher circulating linoleic acid (LA) levels-reflective of dietary LA intake, are associated with a reduced risk of type 2 diabetes. However, genetic variants in the fatty acid desaturase 1 gene (FADS1) may influence individual responses to plant-based fats. We explored whether FADS1 variants influence the relationships of LA and α-linolenic acid (ALA) intakes and nut consumption with plasma phospholipid fatty acid profiles and type 2 diabetes risk in a large-scale cohort study and a randomized controlled trial.

METHODS

In the EPIC-InterAct case-cohort (7,498 type 2 diabetes cases, 10,087 subcohort participants), we investigated interactions of dietary and plasma phospholipid fatty acids and nut consumption with FADS1 rs174547 in relation to incident type 2 diabetes using weighted Cox regression. In PREDIMED (492 participants in the Mediterranean Diet + Nuts intervention group, 436 participants in the control group), we compared changes in plasma phospholipid FAs from baseline to year 1.

RESULTS

In EPIC-InterAct and PREDIMED, nut consumption was positively associated with LA plasma levels and inversely with arachidonic acid, the latter becoming stronger with increasing number of the minor rs174547 C allele (p interaction EPIC-InterAct: 0.030, PREDIMED: 0.003). Although the inverse association of nut consumption with diabetes seemed stronger in participants with rs174547 CC-genotype (HR: 0.73, 95% CI: 0.54-1.00) compared with CT (0.94, 0.81-1.10) or TT (0.90, 0.78-1.05) in EPIC-InterAct, this interaction was not statistically significant.

CONCLUSIONS

FADS1 variation modified the effect of nut consumption on circulating FAs. We did not observe clear evidence that it modified the association between nut consumption and type 2 diabetes risk.

© 2025. The Author(s).

Address: Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, Nuthetal, 14558, Germany.; German Center for Diabetes Research (DZD), Neuherberg, Germany.; International Agency for Research on Cancer, World Health Organization, Lyon, France.; Nuffield Department of Population Health, Cancer Epidemiology Unit, University of Oxford, Richard Doll Building, Old Road Campus, Oxford, UK.; Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK.; Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA (Instituto de Investigación Sanitaria de Navarra), Pamplona, Spain.; CIBER Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain.; Department of Preventive Medicine and Public Health, School of Medicine, University of Valencia, Valencia, Spain.; Department of Public Health, Aarhus University, Aarhus, Denmark.; Department of Public Health, Aarhus University, Aarhus, Denmark.; Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark.; Danish Cancer Institute, Diet, Cancer and Health, Copenhagen, DK-2100, Denmark.; Department of Public Health, University of Copenhagen, Copenhagen, Denmark.; Danish Cancer Institute, Diet, Cancer and Health, Copenhagen, DK-2100, Denmark.; Paris-Saclay University, UVSQ, Inserm, Gustave Roussy, CESP, Villejuif, France.; Division of Cancer Epidemiology, German Cancer Research Center, DKFZ, Heidelberg, Germany.; Clinical Epidemiology Unit, Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy.; Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale Dei Tumori, Milan, Italy.; Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy.; Department of Clinical and Biological Sciences, University of Turin, Turin, Orbassano, Italy.; Unit of Nutrition and Cancer, Epidemiology Research Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, 08908, Spain.; Escuela Andaluza de Salud Pública (EASP), Granada, 18011, Spain.; Instituto de Investigación Biosanitaria Ibs.GRANADA, Granada, 18012, Spain.; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, 28029, Spain.; Department of Epidemiology, IMIB-Arrixaca, Regional Health Council, Murcia University, Murcia, Spain.; CIBER in Epidemiology and Public Health (CIBERESP), Madrid, Spain.; Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, 28029, Spain.; Instituto de Salud Pública y Laboral de Navarra, Pamplona, 31003, Spain.; Navarra Institute for Health Research (IdiSNA), Pamplona, 31008, Spain.; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.; Department of Research, Cancer Registry of Norway, Norwegian Institute of Public Health, Oslo, Norway.; Department of Nutrition, Oslo New University College, Oslo, Norway.; Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Arthur-Scheunert-Allee 114-116, Nuthetal, 14558, Germany. [email protected].; German Center for Diabetes Research (DZD), Neuherberg, Germany. [email protected].; Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany. [email protected].
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