Jared Hoffman1, Vikas Bakshi2, Ishita Parikh2, Janet Guo3, Rachel Armstrong3, Steve Estes4, and Ai-Ling Lin1
1Pharmacology and Nutritional Sciences, University of Kentucky, Lexington, KY, United States, 2University of Kentucky, Lexington, KY, United States, 3Lexington, KY, United States, 4Physiology, University of Kentucky, Lexington, KY, United States
Synopsis
Aging is the perhaps the
greatest risk factor for the development of numerous health concerns, namely
neurological diseases such as Alzheimer’s Disease (AD). Recently, certain
variations in the gut microbiota have been implicated in the development of
neurological disease. We hypothesize that alterations of the gut microbiome
from age may cause dysregulated brain-gut communication, promoting inflammation
and ultimately, disease. Indeed, our preliminary data found old mice to have a
distorted gut microbiota, decreased cerebral blood flow and cognitive deficits,
and distinct levels of certain brain metabolites than the young mice. Synopsis
Aging is the perhaps the
greatest risk factor for the development of numerous health concerns, namely
neurological diseases such as Alzheimer’s Disease (AD). Recently, certain
variations in the gut microbiota have been implicated in the development of
neurological disease. We hypothesize that alterations of the gut microbiome
from age may cause dysregulated brain-gut communication, promoting inflammation
and ultimately, disease. Indeed, our preliminary data found old mice to have a
distorted gut microbiota, decreased cerebral blood flow and cognitive deficits,
and distinct levels of certain brain metabolites than the young mice.
Purpose
The objective of this study
was to examine the influence of the aging process on the brain-gut axis and how
these collectively affect overall neurological function. We used a
multi-disciplinary approach to address brain-gut interaction in reflection on
brain physiology and cognitive function, including neuroimaging, 16s genomic sequencing
of the gut microbiome, cognitive and behavioral testing, and brain metabolomic
assessment.
Methods
Male C57BL/6 mice were
acquired from the National Institute of Aging Caloric Restriction Colony and assigned to two groups, Young (5-6 mo) and Old (18-20 mo), with 19-20 mice per
group. This sample size was selected via a power analysis to ensure a
comparison at a 0.05 level of significance and 90% chance of detecting a true
difference in all measurements between the two groups. The Institutional Animal
Care and Use Committee (IACUC) at the University of Kentucky according to NIH
guidelines approved all experimental procedures. Cerebral blood flow was
determined by magnetic resonance imaging (MRI) on a 7T Clinscan MR scanner in
8-10 mice per group. Fecal samples were collected from each mouse with subsequent
DNA extraction for bacterial metagenomic analysis of 16S ribosomal RNA. Further,
behavior and cognitive function was determined by radial arm water maze (RAWM)
and novel object recognition (NOR). RAWM measured spatial working and reference
memory while novel object recognition measured the behavior of mice via their
affinity to explore new objects over familiar ones. Lastly, metabolomics
profiling of the whole brain was assessed in a separate cohort of old and young
mice (9 mice per group). Following sacrifice of the mice, their brains were sent
to Metabolon (Durhan, NC) for analysis of biochemicals. Metabolon’s standard
solvent extraction method was used to prepare the samples, which were then
equally split for analysis via liquid chromatography/mass spectrometry (LC/MS)
or gas chromatography/mass spectrometry (GC/MS). All statistical analyses were completed using GraphPad Prism (GraphPad,
San Diego, CA, USA). One-tailed Student’s t-test was performed for
determination of differences between groups. Levels of statistical significance
were reached when p < 0.05.
Results
This experiment found many
consequences of aging when comparing the old and young mice groups. Firstly,
the old group demonstrated significantly reduced cerebral blood and variations in their gut micro biome. Next, the old mice demonstrated significantly compromised
learning and behavioral performance in the RAWM and NOR. Lastly, the old mice
saw modified metabolomic profiling of brain metabolites as markers of
inflammation were significantly increased.
Discussion
The results of our study demonstrate the profound effects of
aging, leading elderly individuals susceptible to disease. Our preliminary data
indicate deleterious modifications of the gut microbiota, decreased cerebral
blood flow, distorted cognitive function, and amplified markers of inflammation
in old mice compared to that of young mice due to the aging process.
Collectively, these modifications in the brain and gut indicate a dysfunctional
brain-gut axis leading to, what we believe, increased inflammation and
susceptibility to neurological disease. Remedying inflammation and modulating the gut
microbiome may both be cheap yet effective treatment options in hopes to
decrease the prevalence of neurological disorders.
Conclusion
To conclude, our data indicates that age causes decreased cerebral blood flow, deleterious
modifications of the gut microbiota, inhibited cognitive abilities, and amplified
markers of inflammation in old mice compared to young mice. With this collective knowledge of the aging process, we can create better treatment options in hopes to manipulate and improve the brain-gut axis. In turn, this will decrease our susceptibility to neurological diseases, improving not only lifespan but the quality of life in humans.
Acknowledgements
This study is funded by NIH grant K01AG040164.References
No reference found.