The Clockwork of Microbiome-Based Aging: Tracing the Lifelong Impact of the Gut Microbiome

This article is part three of a four part series on the microbiome and longevity. In our previous article, we have delved into the fascinating world of the gut microbiome and its myriad roles in shaping our overall health. From digestion and metabolism to immune system function, these microscopic inhabitants have a significant impact on our well-being. Yet, one might wonder about the origins of this complex ecosystem within us and the changes it undergoes throughout our lives. In this article, we will systematically explore how we acquire our gut microbiome, the factors influencing its development, and the dynamic journey it embarks on as we traverse the stages of life.

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This article is part three of a four-part series on the microbiome and longevity.

1. From the Gut Up: The Latest Breakthroughs in Microbiome Research
2. Gut Feelings: The Surprising Links Between Gut and Your Body’s Vital Organs
3. The Clockwork of Microbiome-Based Aging: Tracing the Lifelong Impact of the Gut Microbiome
4. Bacterial Botox: Microbiome-Based Interventions for Timeless Health

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Early research, extending as far back as the early 1900s, has documented quantitative assessments of distinct bacterial taxa in the initial stages of life, providing a valuable understanding of the pioneering species that inhabit the neonatal gut (Tissier, H., 1900). 

The precise moment when colonization commences remains a subject of ongoing debate. The prevailing consensus among scientists posits that the fetus develops within a sterile environment, with most of our initial microbiota being acquired during and immediately following birth (Dominguez-Bello et al., 2010). In recent years though, a handful of studies have detected traces of bacterial DNA in the placenta, amniotic fluid surrounding the fetus, and the infant’s first stool (meconium), hinting at the possibility of prenatal colonization (Collado et al., 2016). However, several scientists argue that these findings may be attributed to contamination, intensifying the debate. As a result, the notion of fetal exposure to a more diverse placental microbiota during healthy pregnancies continues to be disputed, although microbial infiltration of the amniotic cavity has been correlated with preterm birth and other unfavorable birth outcomes(Aagaard et al., 2014). 

The Microbiome Before and During Birth

The inaugural encounter with microorganisms transpires during the birthing process, and its characteristics hinge heavily on the chosen mode of delivery. As the amniotic sac ruptures, a deluge of bacteria swiftly colonizes the fetus. Upon navigating through the vaginal canal, the infant becomes enveloped in a microbial veneer. 

Microbiota Differences Between Vaginally and C-Section-Born Infants

Neonates delivered vaginally boast a microbiota teeming with bacteria akin to their mothers’ vaginal, fecal, and skin bacteria, as well as a selection of tenacious microbes from the hospital and nursing staff, such as Lactobacillus species. In contrast, infants born via cesarean (C-) section exhibit diminished diversity and a lower abundance of key microbes, instead displaying an enrichment in skin commensals like Staphylococcus, Streptococcus, and Propionibacterium species (Shao et al., 2019). 

Over time, the discrepancies between the microbiota of vaginally and C-section-born infants gradually diminish, but the precise duration remains a contentious issue. In one investigation, bacteria associated with C-section births persisted in infants delivered by this method for up to two years, indicating that the birth mode could exert long-lasting effects on the microbiota (Chu et al., 2017). The degree to which this influences future health is still debated, although studies propose that children birthed via C-section may face an elevated risk of autoimmune disorders and allergies (Dominguez-Bello et al., 2016; Zhang et al., 2021). 

Re-establishing Microbiome in C-Section Infants and Concerns

Intriguingly, a novel approach to re-establishing the microbiome in C-section infants emerged. In a ground-breaking study, the authors demonstrated that reintroducing a C-section infant to their mother’s vaginal microbes at birth can normalize their microbiome development during the initial year of life (Dominguez-Bello et al., 2016). A more recent and sizable study from the same research group arrived at a comparable finding. The investigators tracked 177 infants from four different nations throughout their first year of life, where 98 were delivered vaginally and 79 by C-section, 30 of whom were swabbed with a maternal vaginal gauze soon after birth. The findings once again demonstrated that reintroducing a newborn delivered via C-section to maternal vaginal microbes immediately after birth helps to restore normal development of the microbiome during their first year of life (Song et al., 2021). 

However, more recently, experts have expressed apprehension regarding the potential transmission of diseases to the child through this method. Considering the burgeoning prevalence of bacterial seeding, The American College of Obstetricians and Gynaecologists advises against its application outside research settings until further information on its safety and benefits is available (“Committee Opinion No. 725,” 2017). 

In another contemporary study, researchers evaluated mother-to-infant microbiota seeding and early-life microbiota development across various maternal and infant niches. They discovered that, in line with previous results, C-section-delivered babies exhibited diminished seeding of infant fecal microbiota by maternal fecal microbes, however colonization with breastmilk microbiota was heightened. Consequently, their findings suggest the existence of alternative pathways for mother-to-infant microbial seeding, which may compensate for one another and ensure the transfer of essential microbes and microbial functions, irrespective of disrupted transmission routes (Bogaert et al., 2023).

Birth to Toddlerhood: The Microbiome in the First 1000 Days of Life

During and immediately following birth, newborns encounter intricate microbial communities in their external surroundings. The first 1,000 days delineate a pivotal window for early childhood growth and development (Robertson et al., 2019). 

Breast Milk, Solid Food and Infant Microbiota

In early infancy, the microbiota’s diversity remains limited, dominated by Bifidobacteria species engaged in the metabolism of human milk oligosaccharides (HMOs) in breastfed infants. Estimates suggest that 25-30% of an infant’s bacterial microbiota originates from breast milk (Pannaraj et al., 2017). Breast milk houses a luscious bacterial mixture, with both prebiotic and probiotic properties. It is mostly characterized by Proteobacteria (predominantly Pseudomonas), Staphylococcus, and Streptococcus, exhibiting a composition distinct from the skin, oral, and gut microbiomes (Li et al., 2017). 

Upon the conclusion of breastfeeding, the introduction of solid foods sparks a rapid escalation in the structural and functional diversity of the infant microbiota (Roager et al., 2023). Simultaneously, the period from the introduction of complementary foods (around six months of age) to the age of two represents a critical phase for child growth. Faecalibacterium prausnitzii, Dorea, and Ruminococcus species are among the most age-discriminatory species from 6 to 24 months of age in healthy infants (Subramanian et al., 2014). These bacteria are adept at degrading glycans, mucin, and complex carbohydrates, as well as generating short-chain fatty acids (SCFAs).

Environmental Exposure and Microbiota Acquisition

However, children’s exposure to a diverse array of bacteria is not limited to food. Unsurprisingly, children also share many microbes with their mother and father, transferred via physical contact (Xiao & Zhao, 2023). Furthermore, every time a child chews an object, hugs/kisses the family pet, or licks a dirty finger a multitude of bacteria find refuge within the body. For instance, a study discovered that children living with dogs had a higher abundance of Bacteroides and SCFA-producing bacteria (Gómez-Gallego et al., 2021) which changed when the dogs were administered a canine probiotic. Another study found that early life exposure to animals can boost the abundance of two types of bacteria—Ruminococcus and Oscillospira—which are associated with a reduced risk of childhood atopy and obesity (the CHILD Study Investigators et al., 2017). 

Impact of Antibiotics on the Infant Microbiota

Finally, although essential to treat life-threatening diseases, the use of antibiotics can influence the ecological succession of the infant microbiota. Antibiotics can undermine the diversity and stability of the developing microbiota in infants, with specific taxa remaining diminished for years following treatment. The long-lasting health implications of antibiotics on the infant microbiota could be significant, as their use in early life has been associated with an increased risk of various diseases, including asthma, inflammatory bowel disease, and allergies (Cox et al., 2014).

An abundance of research has noted that gut microbiota diversity progresses towards a mature, adult-like state by the conclusion of the initial three to five years of life. The composition of the microbiota does not undergo an abrupt shift at any chronological threshold or age; instead, it changes gradually over time. However, there are discernible features of the gut microbiota in different age groups, signifying the distinct developmental stages in the establishment of an individual’s microbial community.

Childhood and Adulthood

As toddlers progress into childhood, the gut microbiome achieves greater stability and assumes a composition that is relatively consistent with that of other adults. The adult gut microbiome is typified by a higher diversity of bacterial species in comparison to kids. This increased diversity can be attributed in part to the introduction of a more varied diet, as well as other lifestyle factors and exposure to a wide range of environmental microorganisms. 

Notably, Bifidobacterium levels decline; these species are typically abundant in the infant gut microbiome and play a pivotal role in breaking down HMOs and bolstering healthy immune function. In adulthood, the gut microbiota is primarily dominated by two major phyla: Firmicutes and Bacteroidetes, with other prevalent phyla including Proteobacteria, Actinobacteria, and Verrucomicrobia(Hollister et al., 2015). These bacteria are involved in the breakdown of complex carbohydrates, proteins, and other nutrients found in a diverse diet. Additionally, specific bacterial genera such as Faecalibacterium, Ruminococcus, Roseburia, and Akkermansia become more abundant, playing critical roles in energy extraction, SCFA production, and maintenance of gut barrier function (Luo et al., 2022; Yatsunenko et al., 2012).

Elderly

In senior adulthood and advanced age, the gut microbiome persists in evolving, and alterations in species composition become increasingly distinct. The aging process instigates substantial transformations in the gut microbiome, characterized by an ongoing reduction in diversity and an escalation in potentially detrimental bacteria. This potentially results in deteriorating overall health and heightened vulnerability to age-related diseases.

Changes in Gut Microbiota Composition in Older Adults

Research has demonstrated a decrease in microbiome diversity and a shift in the gut microbiota composition among older adults. For example, a study involving elderly Irish participants discovered that the abundance of health-enhancing bacteria, such as Bifidobacterium and Akkermansia muciniphila, which uphold gut health and generate SCFAs, was notably lower in senior adults compared to younger individuals (O’Toole & Jeffery, 2015). 

Moreover, older adults tend to exhibit elevated levels of bacteria from the Enterobacteriaceae family, encompassing potentially pathogenic species, and increased levels of Proteobacteria, a group of bacteria correlated with inflammation and infection (Guigoz et al., 2008). Seniors often display diminished levels of Faecalibacterium prausnitzii, a significant butyrate-producing bacterium possessing anti-inflammatory properties (Mueller et al., 2006).

Correlation Between Gut Microbiome and Healthy Aging

Interestingly, a recent study pinpointed three different groups of bacteria within the gut microbiome correlated with healthy aging. Briefly, elderly microbiomes are primarily typified by the diminishing presence of beneficial bacteria (Group 1) and an increase in harmful bacteria (Group 2, including Eggerthella, Desulfovibrio, members of the Enterobacteriaceae family, and disease-associated Clostridium species, as well as Ruminococcus torques). However, another group of beneficial bacteria (Group 3, including Akkermansia, Odoribacter, Butyricimonas, Butyrivibrio, Oscillospira, Christensenellaceae, and Barnesiellaceae) shows an increase with aging, yet a decline in some age-related disorders. These taxa embody taxonomic ‘milestones’ that amplify in abundance during a healthy aging trajectory but dissipate when transitioning to a state of physiological deterioration (Ghosh et al., 2022). 

Centenarians (100+ years)

It is of particular interest that the gut microbiome of centenarians and supercentenarians (those aged 110 or older) may manifest distinct characteristics that contribute to their remarkable longevity. 

A study investigating semi-supercentenarians (aged 105-109) and supercentenarians revealed that these individuals harbored an elevated abundance of health-promoting bacteria, such as Akkermansia, Roseburia, Bifidobacterium, Lactobacillus, and Christensenellaceae, in comparison to their younger elderly peers (Rampelli et al., 2013; Wu et al., 2022). Furthermore, centenarians display a divergent composition of Clostridium clusters relative to younger adults. Several studies have reported an upsurge in Clostridium cluster XIVa and a decline in cluster IV among centenarians, which may impact gut health and SCFA production (Biagi et al., 2010). 

Moreover, current research suggests that individuals with a more bespoke microbiome tend to demonstrate enhanced clinical laboratory results, physical well-being, and mobility, and require fewer medications (Wilmanski et al., 2021). This hints that the specific species composition may possess greater importance than diversity within this demographic. Furthermore, the extraordinary microbiome composition could potentially correlate with a reduced propensity for inflammation and age-associated maladies, thereby contributing to the impressive lifespan of these individuals. Butyrate serves as a crucial source of energy for the cells that compose the inner lining of the human colon (colonocytes). It also induces apoptosis (self-destruction) in colon cancer cells and activates intestinal gluconeogenesis (production of glucose in the body), which is significant for energy balance and diabetes management (De Vadder et al., 2014). 

Microbiome-Based Aging Clocks: The Notion

The distinct patterns of microbiome compositions throughout a lifetime pave the way for predicting age and health status by utilizing the microbiome’s constitution. When researchers delve profoundly into the relationship between the microbiome and aging, they are forging microbiome-based aging clocks. Aging clocks are instruments devised to estimate an individual’s biological age based on biomarkers. Conventionally, aging clocks have been constructed using DNA methylation patterns, telomere length, or blood biomarkers. Nevertheless, contemporary research has redirected the focus toward the gut microbiome, considering its substantial impact on health and aging (Ratiner et al., 2022).

Diverse categories of microbiome-based aging clocks can be developed contingent on the specific microbial attributes and machine learning algorithms employed to predict biological age. Albeit the field is still burgeoning, some approaches for developing microbiome-based aging clocks encompass:

1. Microbiome-Based Diversity Clock: an association between the loss of diversity in the core microbiota groups and an increased frailty index has been repeatedly described. Recent research proposed a diversity-based model for estimating healthy aging, the ‘Hybrid Niche Nature Model’, based on Hubbell’s diversity index, a measure that focuses on species that are rare and most abundant, instead of traditional methods for richness and evenness. The model was suggested to constitute a good predictor of the health status in aged individuals (Sala et al., 2020). However, as the Hybrid Niche Nature Model is a theoretical model to estimate healthy aging, there is no specific mean absolute error (MAE) value -the difference between the predicted age and the real chronological age- provided for it. To determine the MAE, the model would need to be tested and validated on real-world data, comparing the predicted biological ages to the actual biological ages of the individuals in the study. Also, as we previously described, rather than diversity, the uniqueness of the gut microbiome emerged to be associated with better clinical laboratory values, to the point that in people over 84 years of age, this uniqueness appears to be associated with longer life expectancy (Wilmanski et al., 2021). This means that the longitudinal beta-diversity analysis (the difference in diversity of species between people) may provide a more accurate biological age prediction. 
2. Taxonomic composition-based clocks: These aging clocks use the relative abundance of different bacterial taxa at various taxonomic levels (e.g., phylum, class, order, family, genus, or species) to predict age. Machine learning algorithms are trained on datasets containing the taxonomic composition of the gut microbiome from individuals of various ages to create models that can predict age based on the presence and abundance of specific bacterial taxa. A recent study evaluated the ability of oral, gut, and skin microbiomes (from the 16S-V4 rRNA gene amplicon data) to predict adult age. Of the three microbiome signatures specific to body sites, the skin microbiome emerged as the most precise in predicting chronological age, with a mean absolute error of 3.8 years. In contrast, the gut microbiome proved to be the least accurate, with a mean absolute error of 11.5 years (Huang et al., 2020). However, in another recent study, the authors generated a deep neural network machine learning model, using gut metagenome-based taxonomic data including more than 4000 samples of healthy individuals aged 18-90 years. Their most accurate prediction achieved a mean absolute error of 5.91 (Galkin et al., 2020). 
3. Functional Capacity-Based Clocks: Rather than concentrating exclusively on taxonomic composition, these aging clocks take into account the functional capacity of the gut microbiome. They use information regarding the presence and abundance of genes or metabolic pathways implicated in crucial microbial functions. In contrast to microbial taxa, this type of microbiome-based aging clock offers enhanced consistency across cohorts, given that microbiome functions serve as a more reliable ‘common denominator’ characteristic of a healthy condition. These functional aspects are employed to train machine learning algorithms for age prediction, offering insights into the alterations in the functional capacity of the gut microbiome with age and their contribution to the aging process. By examining meta-transcriptomic profiles of approximately 90,000 individuals ranging from 0 to 104 years old, encompassing diverse lifestyle habits and disease states, a new study established a Microbiome-Based Functional Clock with a mean absolute error of 12.98 years (Gopu et al., 2020).
4. Metabolite-based clocks: although an established clock for predicting biological age via bacterial metabolite analysis is yet to be developed, emerging evidence has highlighted the potential of circulating metabolites as promising biomarkers for this purpose. Researchers have identified metabolites associated with biological age by analyzing plasma metabolomic profiles from individuals across a wide age range (18 to 80 years old) (Johnson et al., 2019). Interestingly, several of these molecules have previously been identified as microbe-associated metabolites. Further investigations into secreted metabolites in urine and feces have revealed that microbially modified secondary bile acids, such as isoallo-lithocholic acid and other lithocholic acid isoforms, are abundant in high concentrations in the feces of centenarians (Sato et al., 2021). By analyzing the abundance and composition of these metabolites, scientists can create aging clocks that capture the functional output of the gut microbiome, thereby offering a novel approach to predicting biological age.
5. Multi-omics-based clocks: through the integration of multiple types of omics data such as metagenomics, metatranscriptomics, and metabolomics, multi-omics-based aging clocks offer a more comprehensive understanding of the gut microbiome’s involvement in the aging process, potentially resulting in more precise and holistic age predictions. In a recent study, researchers attempted to predict age using multiple microbial omics, integrating taxonomic and functional information obtained from stool metagenomics. After accounting for geographical covariates, the combined model based on bacteria species and functional pathways yielded the best prediction of chronological age with an average mean absolute error of 8.33 years (Chen et al., 2022). The result suggests that the different types of microbiome-based aging clocks have the potential to complement each other, allowing for a more comprehensive understanding of the gut microbiome’s role in the aging process.

Microbiome-based aging clocks offer several potential advantages over other aging clocks, despite the epigenetic clock being regarded as the most precise representation of aging decline over time. Microbiome clocks can provide a more comprehensive view of an individual’s health status, as the gut microbiome is involved in various physiological processes, including metabolism, immunity, and inflammation (Levy et al., 2022). By taking a holistic approach, new insights into the underlying mechanisms of aging can be gained, and potential therapeutic targets for promoting healthy aging can be identified. Moreover, as the gut microbiome can be “quickly” modulated through interventions like diet and lifestyle changes, microbiome-based aging clocks may prove useful in assessing the efficacy of such interventions in improving an individual’s health and longevity. This personalized approach can pave the way for tailored interventions aimed at slowing down the aging process or improving age-related health outcomes. Therefore, a combination of host- and microbiome-derived aging clocks holds great potential for reflecting precise and accurate biological aging.

The Road Ahead: Unlocking the Potential of the Gut Microbiome for Healthy Aging

In conclusion, the human gut microbiome undergoes dynamic changes throughout an individual’s lifetime, with distinct microbial communities observed across various age groups. It is noteworthy that beyond chronological age, a multitude of factors, including genetics, dietary habits, lifestyle choices, and environmental exposures, significantly impact the maturation and modulation of the gut microbiome.

Recent studies have shed light on the potential of microbiome-based aging clocks to predict biological age accurately. These clocks incorporate multiple types of omics data to provide a more comprehensive understanding of the underlying mechanisms of aging. With further research and refinement of these aging clocks, we may soon have a more accurate understanding of the biological age of individuals and the potential to develop targeted interventions for improved health outcomes. 

Nevertheless, population-level interventions aimed at modulating the gut microbiome have already emerged as promising strategies for promoting healthy aging. In our next article, we will burrow into microbiome-based interventions and explore their potential to enhance overall health and longevity.

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