Bibliographic Details
| Title: |
Sialic acid, the secret gift for the brain. |
| Authors: |
Liu, Fan1 (AUTHOR), Simpson, Anna Bella1 (AUTHOR), D'Costa, Esmée1 (AUTHOR), Bunn, Fanny Sophia1 (AUTHOR), van Leeuwen, Sander S.2 (AUTHOR) s.s.van.leeuwen@umcg.nl |
| Source: |
Critical Reviews in Food Science & Nutrition. 2023, Vol. 63 Issue 29, p9875-9894. 20p. |
| Subjects: |
Sialic acids, Dietary supplements, Breast milk, Neural development, Alzheimer's disease, Homeostasis, Neurofibrillary tangles |
| Abstract: |
The human brain grows rapidly in early life which requires adequate nutrition. Human milk provides optimal nutrition for the developing brain, and breastfeeding significantly improves the cognition development of infants. These benefits have been largely attributed to human milk oligosaccharides (HMOS), associated with sialic acid (Sia). Subsequently, sialylated HMOS present a vital source of exogenous Sia to infants. Sialic acid is a key molecule essential for proper development of gangliosides, and therefore critical in brain development and function. Recent pre-clinical studies suggest dietary supplementation with Sia or sialylated oligosaccharides enhances intelligence and cognition performance in early and later life. Furthermore, emerging evidence suggests the involvement of Sia in brain homeostasis and disbalance correlates with common pathologies such as Alzheimer's disease (AD). Therefore, this review will discuss early brain health and development and the role of Sia in this process. Additionally, studies associating breastfeeding and specific HMOS to benefits in cognitive development are critically assessed. Furthermore, the review will assess studies implying the potential role of HMOS and microbiota in brain development via the gut-brain axis. Finally, the review will summarize recent advances regarding the role of Sia in neurodegenerative disease in later life and potential roles of dietary Sia sources. [ABSTRACT FROM AUTHOR] |
|
Copyright of Critical Reviews in Food Science & Nutrition is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) |
| Database: |
Engineering Source |
