Selenium supplementation has beneficial and detrimental effects on immunity to influenza vaccine in older adults

Background & aims: Mortality resulting from influenza (flu) virus infections occurs primarily in the elderly through declining immunity. Studies in mice have suggested beneficial effects of selenium (Se) supplementation on immunity to flu but similar evidence is lacking in humans. A dietary intervention study was therefore designed to test the effects of Se-supplementation on a variety of parameters of anti-flu immunity in healthy subjects aged 50–64 years. Methods: A 12-week randomized, double-blinded, placebo-controlled clinical trial (ClinicalTrials.gov NCT00279812) was undertaken in six groups of individuals with plasma Se levels <110 ng/mL. Four groups were given daily capsules of yeast enriched with 0 μg Se/day (SeY-0/d; n = 20), 50 μg Se/d (SeY-50/d; n = 18), 100 μg Se/d (SeY-100/d; n = 21) or 200 μg Se/d (SeY-200/d; n = 23). Two groups were given onion-containing meals with either <1 μg Se/d (SeO-0/d; n = 17) or 50 μg Se/d (SeO-50/d; n = 18). Flu vaccine was administrated at week 10 and immune parameters were assessed until week 12. Results: Primary study endpoints were changes in cellular and humoral immune responses. Supplementation with SeY and SeO affected different aspects of cellular immunity. SeY increased Tctx-ADCC cell counts in blood (214%, SeY-100/d) before flu vaccination and a dose-dependent increase in T cell proliferation (500%, SeY-50/100/200/d), IL-8 (169%, SeY-100/d) and IL-10 (317%, SeY-200/d) secretion after in vivo flu challenge. Positive effects were contrasted by lower granzyme B content of CD8 cells (55%, SeY-200/d). SeO (Se 50 μg/d) also enhanced T cell proliferation after vaccination (650%), IFN-γ (289%), and IL-8 secretion (139%), granzyme (209%) and perforin (190%) content of CD8 cells but inhibited TNF-α synthesis (42%). Onion on its own reduced the number of NKT cells in blood (38%). These effects were determined by comparison to group-specific baseline yeast or onion control groups. Mucosal flu-specific antibody responses were unaffected by Se-supplementation. Conclusion: Se-supplementation in healthy human adults with marginal Se status resulted in both beneficial and detrimental effects on cellular immunity to flu that was affected by the form of Se, supplemental dose and delivery matrix. These observations call for a thorough evaluation of the risks and benefits associated with Se-supplementation

The SENS algorithm—a new nutrient profiling system for food labelling in Europe

International audienceBackground/objectives In response to the European regulation on nutrition and health claims, France proposed in 2008 the SAIN,LIM profiling system that classifies foods into four classes based on a nutrient density score called ‘SAIN’, a score of nutrients to limit called ‘LIM’, and one primary threshold on each score. We present here the SENS algorithm, a new nutrient profiling system adapted from the SAIN,LIM to be operational for simplified nutrition labelling in line with the European regulation on food information to consumers. Subjects/methods The main changes made to SAIN,LIM to get SENS were to introduce food categories and sub-categories (‘Beverages’, ‘Added Fats’ and ‘Other Solid Foods’ sub-categorised into ‘cereals’, ‘cheese’, ‘other dairy products’, ‘eggs’, ‘fish’ and ‘others’), reduce the number of nutrients, introduce category-specific nutrients and category-specific weighting for some nutrients, replace French recommendations with European reference intakes, and add secondary thresholds. Each food and non-alcoholic beverage from the 2013-CIQUAL French composition database (n = 1065) was assigned one SENS class. Distribution of foods according to the four SENS classes was described by food groups (n = 26). Results The SENS classification was consistent with the recommendations to consume large amounts of whole grains, vegetables and fruits, and moderate intake of fats, sugars, meats, caloric beverages and salt. For most groups (19/26), foods were distributed across at least three SENS classes. Conclusions The SENS is a nutrition-sensitive system that discriminates foods between and within food categories. It preserves the strengths of the initial SAIN,LIM while making it operational for simplified nutrition labelling in Europe