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Aging, gut microbiome, and lipid metabolism

Research Article

Age-related gut microbiome changes are reflected in serum lipidome.

About the author


Olga (Olya) Vvedenskaya
Sci. Communications Officer

Dr. Dr. Olya Vvedenskaya studied medicine, and further obtained her PhD in the field of molecular oncology. She loves to deliver scientific messages in a clear and accessible manner.

Resources


Aging and sarcopenia…

Siddharth et al. | Aging (2017)


Mouse lipidomics reveals inherent flexibility…

Surma et al. | SciRep (2021)


Systematic screening for novel lipids by…

Papan et al. | Anal. Chem. (2014)


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Summary

• Aging processes affect gut microbiome
• Change of gut microbiome impacts lipid metabolism
• Negative changes in lipid metabolism correlate with muscle function decline

According to the WHO, at the biological level, aging results from the impact of the accumulation of a wide variety of molecular and cellular damage over time. Aging includes changes in various aspects of host functions, encompassing cellular processes (leading to oxidative stress and senescence), as well as a gradual deterioration in the functioning of most organs, such as skin aging, and metabolic homeostasis. Interestingly, the influence of the gut microbiota on several age-related aspects, especially lipidome, remains a relatively unexplored area of research.

Siddharth and colleagues conducted a comprehensive study on Wistar rats that exhibit symptoms of sarcopenia, that is a loss of skeletal muscle and strength, when they reach 2 years of age. These rats served as a model to define the metabolic fingerprint, microbiome changes, and particular physiological parameters associated with aging and sarcopenia. The research team analyzed age-specific characteristics within the gut microbial communities among rats at 8 months (adult), 18 months (adult-pre-sarcopenic), and 24 months (adult sarcopenic), as well as age-related shifts in the metabolic capabilities of these microbes.

Study design. Healthy, pre-sarcopenic, and sarcopenic aged rates were used in the study. Fecal 16S analysis, physiological characterization, serum proteomics, and serum lipidomics analyses were performed on all groups of rats.

The gut microbiome represents an ecosystem influenced by a myriad of environmental factors such as diet, medications, and exposure to pathogens, as well as host-related factors including immunity. The researchers analyzed the microbiota’s composition across different age groups, intending to identify pivotal bacterial species linked to the aging process.

To achieve this, the researchers measured the community richness of fecal microbiomes. The analysis of microbial community members, specifically focusing on the Sutterella to Barnesiella ratio showed that this ratio tends to increase with advancing age. Remarkably, the increase in this gut microbiome feature was found to be closely associated with aging-related characteristics, particularly concerning lean mass, vitamin B12 levels, lipid metabolism, and gastrocnemius muscle mass. 

Microbial changes in rats during aging/sarcopenia. The shift in Sutterella to Barnesiella ratio in rodent gut microbiome during aging.

Microbial changes in rats during aging/sarcopenia. The shift in Sutterella to Barnesiella ratio in rodent gut microbiome during aging.
Siddharth et al., Aging, 2017 Jul 17;9(7):1698-1720, 10.18632/aging.101262

The authors further analyzed the proteome and lipidome profiles of aging rats’ serum. Using proteomics data, they detected changes in dietary metabolism, potentially mediated through the influence of vitamin B12 and folate, which is connected to the aging phenotype.

The shotgun mass spectrometry lipidome analysis allowed the authors to detect, identify, and quantify 122 lipid species. Data visualization and analysis of lipid species across the different age groups revealed no distinct separation between the 8-month and 18-month groups. This observation was further confirmed through statistical comparisons, which showed no statistically significant differences in the levels of lipid species between the 8-month and 18-month groups.

However, a clear separation emerged when comparing lipidomes of the 18-month and 24-month groups of aging rats. Notably, five lipid species exhibited statistically significant differences between these two groups. Specifically, levels of two lysophosphatidylcholines (LPC 20:5 and LPC 20:3) decreased with aging, while three lipids, lysophosphatidylinositol (LPI 16:0), phosphatidylcholine (PC 37:4), and sterol ester (SE 20:4), increased with aging. These changes in PC and LPC levels align with the observed alterations in Vitamin B12 and folate status.

Analysis and visualization of lipidomics data. A In the multivariate data analysis plot of a full lipidome, we observe a distinct division between the 18-month and 24-month samples. No separation between the 8-month to 18-month and 8-month to 24-month comparisons is observed. B The lipid species that show statistically significant differences. Arrow up - upregulation, arrow down – downregulation. No arrow indicated no significant differences.

Analysis and visualization of lipidomics data. A In the multivariate data analysis plot of a full lipidome, a distinct division between the 18-month and 24-month samples was observed. No separation between the 8-month to 18-month and 8-month to 24-month comparisons is observed. B The lipid species that show statistically significant differences. Arrow up – upregulation, arrow down – downregulation. No arrow indicated no significant differences.
Siddharth et al., Aging, 2017 Jul 17;9(7):1698-1720, 10.18632/aging.101262

Further, the authors examined the associations between lipid levels and physiological parameters. The reduction in gastrocnemius muscle mass observed with age correlated with certain lipid levels. Specifically, there was a positive correlation between gastrocnemius muscle mass and LPC 20:3, which exhibited a decrease in the 18-month to 24-month age group. Similarly, the sciatic response amplitude, an indicator for axon loss, decreased in the 8-24-months and 18-24 months groups, and showed positive correlations with decreased levels of LPC 20:5 and LPC 20:3, while exhibiting negative correlations with increased levels of PC 37:4 and SE 20:4. These findings suggest that lipid metabolism may be involved in the development of the sarcopenic phenotype in these rats.

An infographic depicting sciatic response that declines in aging mice.

LPC 20:5, LPC 20:3, and PC 37:4 emerged as some of the most strongly correlated lipid species, pointing towards a potential connection with microbial metabolism of vitamin B12 and folate. A decrease in LPC 20:5 has previously been shown in individuals with obesity. Furthermore, both LPC 20:5 and LPC 20:3 have previously shown negative correlations with BMI in the context of obesity. The observation of these lipids being associated with a sarcopenic phenotype suggests that the microbiome may play a role in regulating lipid metabolism in sarcopenia, obesity, or aging.

Correlation between statistically different lipid species and measured physiological parameters. The positive correlation is observed in gastrocnemius muscle mass and LPC 20:3, and sciatic response amplitude and LPC 20:5 and LPC 20:3. The negative correlation is observed in sciatic response amplitude and PC 37:4 and SE 20:4.

Correlation between statistically different lipid species and measured physiological parameters. The positive correlation is observed in gastrocnemius muscle mass and LPC 20:3, and sciatic response amplitude and LPC 20:5 and LPC 20:3. The negative correlation is observed in sciatic response amplitude and PC 37:4 and SE 20:4.
Siddharth et al., Aging, 2017 Jul 17;9(7):1698-1720, 10.18632/aging.101262

The comprehensive analysis of microbial, proteomic, and lipidomic biomarkers involved in the aging process indicates that the microbiota’s influence on dietary metabolism may have an effect on certain aspects of aging-related effects. This, in turn, opens up new avenues for nutritional interventions to explore in the context of age-related conditions, including sarcopenia.

In this study, the researchers explored gut microbiome, muscle physiology, serum protein and lipid markers to establish a profile of age-related changes in both the gut microbiome and host physiology. This research paves the way to identifying the molecular mechanisms that drive microbiome-associated aging and offers potential directions for therapeutic interventions to promote healthy aging.

Lipotype Lipidomics technology can be used to characterize changes in serum lipidome in pathological processes such as systemic inflammation, cardiovascular diseases, obesity, and many others.

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