Researchers, from the Harvard T.H. Chan School of Public Health in collaboration with investigators from Rovira i Virgili University and the University of Navarra, Spain, used machine learning models, a subset of artificial intelligence, to identify more precisely the components in walnuts that may be responsible for potentially reducing the risk of type 2 diabetes and cardiovascular diseases - two of the leading causes of death in the U.S.
This study, supported by the California Walnut Commission and published in the Journal of Nutrition, used a novel machine learning model to identify 19 metabolites that were associated with walnut consumption. The body forms specific metabolites based on what food is consumed. The walnut metabolite profile was associated with a 17% lower risk of type 2 diabetes and 29% lower risk of cardiovascular disease. This is the first study to examine the association between walnut metabolites and the risk of cardiometabolic diseases, contributing to the three decades of existing research on walnuts and heart health.
"With data-driven technologies, we are able to enhance our understanding of the relationship between diet and disease and take a personalized approach to nutrition which will lead to better prevention and management of various health conditions," says Dr. Marta Guasch-Ferré, a Research Scientist at the Department of Nutrition at Harvard T.H. Chan School of Public Health, Instructor in Medicine at Harvard Medical School and Brigham and Women's Hospital, and lead investigator of this research.
In this study, we revealed the unique metabolomic signature of walnuts, which brings us one step closer to understanding "how" walnuts are good for our health. These cutting-edge technologies are shaping the future of nutrition recommendations."
Dr. Marta Guasch-Ferré, Research Scientist
Researchers examined data from 1,833 participants of the PREvención con DIeta MEDiterránea (PREDIMED) study, a large-scale, multi-year study that took place in Spain and looked at the effects of a Mediterranean diet in the prevention of cardiovascular disease among people at high risk for heart disease. Participants were aged 55-80 and followed one of three diets: 1) Mediterranean diet supplemented with mixed nuts (50% walnuts, 25% almonds, and 25% hazelnuts); 2) Mediterranean diet supplemented with extra-virgin olive oil; or 3) low-fat diet. The metabolites in walnuts form the walnut metabolite profile associated with a reduction in type 2 diabetes and cardiovascular disease.
These findings further emphasize the connection between walnut consumption as part of a healthy diet and cardiometabolic health. New tools as used in this epidemiological study will help identify links between diet and disease. However, the results do not prove cause and effect. More research is needed in other populations since this study was focused on older Spanish adults only. In addition, given the field of metabolomics is rapidly evolving, future studies will be needed to identify additional biomarkers of walnut intake that were not pursued in this study as well as to understand individual metabolic responses after consuming walnuts.
The California Walnut Commission (CWC) supported this research. The CWC has supported health-related research on walnuts for more than 30 years with the intent to provide knowledge and understanding of the unique health benefits associated with consuming walnuts. While the CWC does provide funds and/or walnuts for various projects, all studies are conducted independently by researchers who design the experiments, interpret the results and present evidence-based conclusions. The CWC is committed to scientific integrity of industry-funded research.
The California walnut industry is made up of over 4,800 growers and more than 90 handlers (processors). The growers and handlers are represented by two entities, the California Walnut Board (CWB) and the California Walnut Commission (CWC).
Guasch-Ferré, M., et al. (2020) Walnut Consumption, Plasma Metabolomics, and Risk of Type 2 Diabetes and Cardiovascular Disease. The Journal of Nutrition. doi.org/10.1093/jn/nxaa374.