Risk assessment of nutrients: There must be a threshold for their effects.

Nutrients serve physiological functions in a dose-dependent manner and that needs to be recognized in risk assessment. An example of the consequences of not properly considering this can be seen in a recent assessment by the European Food Safety Authority (EFSA). EFSA concluded in 2022 that the intake of added and free sugars should be "as low as possible in the context of a nutritionally adequate diet". That conclusion of EFSA is based on the effects on two surrogate endpoints for an adverse effect found in randomized controlled trials with high sugars intake levels: fasting glucose and fasting triglycerides. The lowest intake levels in these trials were around 10 energy% and at this intake level there were no adverse effects on the two outcomes. This indicates that the adverse effects of sugars have an observable threshold value for these two endpoints. The most appropriate interpretation from the vast amount of data is that currently no definitive conclusion can be drawn on the tolerable upper intake level for dietary sugars. Therefore, EFSA's own guidance would lead to the conclusion that the available data do not allow the setting of an upper limit for added sugars and hence, that more robust data are required to identify the threshold value for intake of sugars.

Investigating the gut microbiome and metabolome following treatment with artificial sweeteners acesulfame potassium and saccharin in young adult Wistar rats.

To elucidate if artificial sweeteners modify fecal bacterial composition and the fecal and plasma metabolomes, Wistar rats from both sexes were treated for 28 days with acesulfame potassium (40 and 120 mg/kg body weight) and saccharin (20 and 100 mg/kg body weight). Targeted MS-based metabolome profiling (plasma and feces) and fecal 16S gene sequencing were conducted. Both sweeteners exhibited only minor effects on the fecal metabolome and microbiota. Saccharin treatment significantly altered amino acids, lipids, energy metabolism and specifically, bile acids in the plasma metabolome. Additionally, sex-specific differences were observed for conjugated primary and secondary bile acids. Acesulfame potassium treated male rats showed larger alterations in glycine conjugated primary and secondary bile-acids than females. Other changes in the plasma metabolome were more profound for saccharin than acesulfame potassium, for both sexes. Changes in conjugated bile-acids in plasma, which are often associated with microbiome changes, and the absence of similarly large changes in microbiota suggest an adaptative change of the latter, rather than toxicity. Further studies with a high resolution 16S sequencing data and/or metagenomics approach, with particular emphasis on bile acids, will be required to explore the mechanisms driving this metabolic outcome of saccharin in Wistar rats.

A chemical-specific adjustment factor for human interindividual differences in kinetics for glutamates (E620-625).

Use of a default methodology for establishment of a health-based guidance value (HBGV) resulted in a group acceptable daily intake (ADI) for glutamates (E620-625) below the normal dietary glutamate intake, and also lower than the intake of free glutamate by breast fed babies. Use of a chemical-specific adjustment factor (CSAF) may overcome this problem. The present study investigates the interindividual human variability in glutamate plasma and brain levels in order to define a CSAF for the interindividual variation in kinetics, a HKAF, for glutamates. Human clinical data on plasma glutamate levels available from different groups of subjects at Mitsui Memorial Hospital as well as literature data on plasma and brain-related glutamate levels were collected and analysed. The median HKAF value obtained amounted to 2.62-2.74 to 2.33-2.52 for plasma derived values and to 1.68-1.81 for brain derived values. Combining these values with the CSAF for the interspecies differences in kinetics of 1 and the default factors for interspecies and interindividual differences in dynamics of 2.5 and 3.16 results in an overall CSAF of 16-20. Using this CSAF will result in a HBGV for glutamate that is no longer below the acceptable range of oral intake (AROI).