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The microbiota - polyphenol interplay in neurodegenerative disease

 
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  • The microbiota - polyphenol interplay in neurodegenerative disease

Neurodegenerative diseases (NDs) are a diverse group of disorders characterised by slow progressive loss of neurons in the central nervous system (CNS) which leads to deficits in specific brain functions performed by the affected regions, such as memory, movement and cognition.

Ageing is one of the greatest known risk factors for developing ND and as the general population ages, these disorders present a significant challenge to health and aged care. In 2017, more than one in seven Australians were aged 65 and over.[1]

Common examples of NDs are Alzheimer’s disease (AD) and Parkinson’s disease (PD). AD accounts for 80% of dementia cases, which affects one in 10 individuals aged 65 years and over and was the second leading cause of death in Australia in 2013.[2]

Currently, about 110,000 Australians are living with PD.[3] Around 18% of these individuals are working age, however, the prevalence increases threefold after the age of 65 and is expected to increase dramatically as the population ages.[3] Common NDs also include amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS). Due to a lack of effective curative treatment options, various potential preventative factors are being sought, including modifiable lifestyle factors such as diet.

Role of microbiota in ND disease

Ageing is related to specific changes in intestinal microbial diversity that may affect health outcomes in the elderly.

As discussed in a newly published review, emerging evidence indicates that changes in the composition of the microbiota may contribute to the onset of ND that increase with age, including AD and PD.[4]

The connection between the microbiota and the CNS, the gut-brain-axis, is well established. Communication between the gut and the brain involves numerous pathways. The microbiota also produces neurotransmitters and neuropeptides, including short-chain fatty acids (SCFAs), tryptophan, gamma-aminobutyric acid (GABA) and brain-derived neurotrophic factor (BDNF), which directly influence brain function.[4] Alteration of the gut-brain-axis has been associated with neurological disorders and ND.[4]

Gut microbiota composition can be influenced by dietary ingestion of bioactive molecules such as prebiotics, probiotics and polyphenols.[4]

Polyphenols

Polyphenols are naturally occurring compounds in many berries, fruits and vegetables, as well as cereals, tea, coffee, cocoa, and wine. Polyphenols suppress neuroinflammation and protect neurons against oxidative stress and inflammatory injury, thus promoting memory, learning, and cognitive functions.[4] However, the majority of dietary polyphenols are not easily absorbed in their native form and rely on intestinal transformation into bioactive metabolites.[4]

Polyphenol-microbiota interplay

Gut microbiota and dietary polyphenols have a symbiotic relationship: the microbiota enzymatically transforms polyphenols to improve bioavailability, while polyphenols modulate microbial composition by enhancing the growth of beneficial bacteria and inhibiting the growth of pathogens, thus exhibiting a prebiotic-like effect.[4]

The impact of polyphenols on intestinal microbial composition supports the hypothesis that maintaining microbial homeostasis by modulating the diet is important to maintain healthy brain function throughout life. Evidence suggests that this approach may be used as a novel therapeutic in the prevention of neurodegeneration.[4]

References

  1. Australian Institute of Health and Welfare (AIHW). Older Australia at a glance. Viewed 12 November 2018, [Source]
     
  2. Australian Institute of Health and Welfare (AIHW). Australia’s health 2016. Australia’s health series no. 15. Cat. no. AUS 199. Canberra: AIHW.[Source]
     
  3. Parkinson’s Australia. Statistics about Parkinson’s. Viewed 8 November 2018, [Source]
     
  4. Filosa S, Di Meo F, Crispi S. Polyphenols-gut microbiota interplay and brain neuromodulation. Neural Regen Res 2018;13(12):2055-2059. [Abstract]

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