Is inflammageing influenced by the microbiota in the aged gut? A systematic review
Introduction
The elderly population, particularly the oldest old group, is growing very rapidly. It was estimated that in 2020, for the first time in human history, people aged 60 and older will outnumber the children aged five and younger (https://www.thelancet.com/series/ageing). Moreover, by 2050, the elderly are expected to comprise more than one-fifth of the world's population (Lutz et al., 2008). These unprecedented demographic transformations have resulted in the emergence of new trends in epidemiology, with the rise of chronic diseases (Ezzati et al., 2002). Indeed, one of the most prominent manifestations of ageing - in both humans and non-human animals - is low grade chronic inflammation (LGCI), known as inflammageing (Fulop et al., 2017; Lencel and Magne, 2011; Chung et al., 2019). Serum levels of pro-inflammatory cytokines including, but not limited to, interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) are commonly elevated in the elderly when compared to young persons, even in healthy persons, in the absence of overt infection (Bruunsgaard and Pedersen, 2003). This LGCI is thought to underlie many age-related manifestations, including increased vulnerability for diseases, morbidity, and mortality (De Martinis et al., 2006). There is supportive evidence for a direct role of LGCI in the development of disability and dependence in elderly persons (Hubbard et al., 2009; Schmaltz et al., 2005). As a result, chronic inflammatory conditions commonly encountered in the geriatric population have become major health concerns.
Several possible sources of LGCI observed during ageing have been postulated, including, among others, cell senescence, dysregulation of innate immunity, and changes in gut integrity (Lasry and Ben-Neriah, 2015; Licastro et al., 2005; Buford, 2017). In the gut, the intestinal epithelial cells represent the first barrier against invading microorganisms. They secrete antimicrobial substances such as mucins and defensins, and are able to sense pathogens (via recognition by Toll-like receptors), sample them and transfer the information to immune cells (Miron and Cristea, 2012; Kraehenbuhl and Neutra, 2000). However, several studies have reported major alterations in immune responses of the aged gut in both humans and non-human animal models (Dicarlo et al., 2009; Biagi et al., 2013; Larbi et al., 2008; Simioni et al., 2007). For instance, a reduction in the secretion of mucin by intestinal epithelial cells and a greater permeability of mucosal membranes have been observed in older persons (Tran and Greenwood-Van Meerveld, 2013). This condition facilitates the entry of microorganisms into the mucosal layers, resulting in the release of heightened levels of lipopolysaccharides, which, in turn, may lead to pro-inflammatory signaling through pattern recognition receptors (Chassaing and Gewirtz, 2014; Cani et al., 2008; Cerf-Bensussan and Gaboriau-Routhiau, 2010; Mehal, 2013). In this perspective, increasing evidence has implicated age-related deterioration of the gut barrier against bacteria as contributing to inflammaging and age-related chronic health conditions (Chassaing and Gewirtz, 2014).
Emerging studies have shown that perturbations in gut microbiota configuration could play a role on mouse health and disease. Indeed, transplantation of fecal matter from twins discordant for obesity into germ-free (GF) mice resulted in variation of the mice's body composition measurements that were associated with differences in meta-transcriptome profiles of the transplanted microbial communities', suggesting a role of the gut microbiota in obesity (Ridaura et al., 2013). Also, changes in aged gut microbiota in mice is associated with modifications in lipid classes and in fatty acid profile (in decreasing polyunsaturated fatty acids and in increasing monounsaturated fatty acid content) in the cortex, which has been reported to have a profound impact on brain physiology (Albouery et al., 2019). Another pathologic situation that is impacted by gut microbiota is Parkinson's disease, whose major risk factor is the clustering of α-synuclein in brain neurons. Mice that overexpressed α-synuclein developed α-synuclein clusters with corresponding defects in motor function and gut motility, while genetically-modified GF mice overexpressing α-synuclein show significantly fewer α-synuclein clusters. Moreover, fecal samples from Parkinson's patients increase motor dysfunction in mice, revealing the causative role of the gut microbiota in α-synuclein clustering and the resulting pathology (Sampson et al., 2016). More so, the sequence of bacterial 16S rRNA from fecal samples of transgenic mice expressing amyloid-β precursor protein - a critical risk factor for Alzheimer's disease - was found to have a remarkable shift in the gut microbiota as compared to non-transgenic wild-type mice. The colonization of GF amyloid-β precursor protein transgenic mice with microbiota from conventionally-raised amyloid-β precursor protein transgenic mice increased cerebral amyloid-β pathology, while colonization with microbiota from wild-type mice was less effective in increasing cerebral amyloid-β levels (Harach et al., 2017).
Also, in humans, dysbiosis in gut microbiome is known to be an important contributing factor of age-associated pathological states. Indeed, many pathological conditions including cardiovascular diseases, insulin resistance, diminished motor activity, and hepatic steatosis have been associated with gut dysbiosis (Nicholson et al., 2012; Burcelin et al., 2011). Moreover, age-related changes in gut microbiota have been shown to impact gut-brain axis in humans, thereby leading to diseases of the central nervous system such as anxiety, multiple sclerosis, depression, neurodegeneration and Alzheimer's disease (Collins et al., 2012; Luna and Foster, 2015; Friedland, 2015). The microbiome of older people suffering from Alzheimer's disease shows a lower proportion and prevalence of bacteria with potential to synthesize butyrate and a corresponding increase in the proportion of taxa that are responsible for proinflammatory states (Haran et al., 2019).
Thus far, our understanding of the effects of multiple deregulations in the gut microbiota in mediating inflammageing with advancing age is incomplete. In the aged population, there is reduction in the number of intestinal commensal bacteria that maintain immune tolerance in the gut (Claesson et al., 2012; Kumar et al., 2007), while most of the opportunistic bacteria whose numbers are generally elevated with age are known to stimulate intestinal inflammation (Kelly et al., 1994; Pamer, 2007). Indeed, Toward et al. (2012) reported an age-related decrease in the abundance of anti-inflammatory microbiota including Bifidobacterium spp. and Faecalibacterium prausnitzii. In contrast, the presence of pro-inflammatory microbiota, such as Streptococcus spp., Staphylococcus spp., Enterococcus spp., and Enterobacter spp. was found to increase with age (Toward et al., 2012). Also, a decline of bifidobacterial with a corresponding increase of Bacteroides has been observed with ageing (Hopkins et al., 2002; Hopkins et al., 2001; Biagi et al., 2010; Claesson et al., 2011). On the other hand, He et al. (2004) reported an age-related upregulation of Ruminococcus, Eubacterium, Lactobacillus and Enterococcus, contrasting with a reduction of Faecalibacterium and Bacteroides both anti-inflammatory microbiota reported to prevent intestinal inflammation (Mazmanian et al., 2008) through suppression of the pro-inflammatory IL-17 production and the induction of Foxp3+ regulatory T cells that produce IL-10 (Round and Mazmanian, 2010). In this framework, the current systematic review aimed at evaluating the literature on the effects of aged gut microbiota on inflammageing.
Section snippets
Literature search
The literature databases including PubMed [search key: ((“Inflammation”[Mesh]) OR Inflammation) OR Interleukin*) OR Cytokine) OR infection) OR IL6) OR IL10) OR IL1) OR IL17) OR IL8) OR IL23) OR Interferon*) OR “tumor necrosis factor alpha”) OR “Granulocyte macrophage colony stimulating factor”) OR Lymphokine) OR Chemokine) OR Prostaglandin)) AND ((“Immunity”[Mesh]) OR Immunity) OR “Immune system”) OR (“T cell” OR “T cells”)) OR (“B cell” OR “B cells”)) OR (“dendritic cell” OR “dendritic
Literature search
A potential total of 2973 articles were generated: 927 in PubMed, 921 in Web of Science, and 1125 in Scopus. Duplicates (n = 871) were removed and, excluding articles based on title and abstract, a total of 10 articles were retained. After analysis of the full texts, 5 articles were included. The reference lists of the included articles were screened, and a forward search was also performed using articles that have cited the included articles, bringing the total number to 7 articles. Six out of
Discussion
The gut microbiota do not age per se, however, with ageing, important perturbations in the gut microbiota have been underlined and a growing body of evidence has implicated, among others, a reduced intestinal integrity as contributing to gut dysbiosis and its associated inflammation (Nagpal et al., 2018). Indeed, it has been speculated that the intestinal epithelium - that acts as a barrier between gut microbes and systemic circulation - might play a crucial role in the association of
Conclusion
In conclusion, ageing perturbs the gut microbiota with a shift in bacterial composition toward pro-inflammatory phenotypes. In the animal studies, age-related alteration in gut microbiota contributed to a chronic low-grade inflammatory state. Indeed, Parabacteroides, Mucispirillum, Clostridium and Sarcina positively associate with the pro-inflammatory MCP-1 while Akkermansia, Oscillospira, Blautia and Lactobacillus negatively correlate with MCP-1. Furthermore, “aged”-type microbiota were
Author contributions
Conceptualization, Rose Njemini, Tony Mets, Ivan Bautmans; Data curation, Cabirou Mounchili Shintouo, Rose Njemini; Formal analysis, Cabirou Mounchili Shintouo, Rose Njemini, David Beckwee; Funding acquisition, Rose Njemini; Investigation, David Beckwee, Rose Njemini, Cabirou Mounchili Shintouo, Stephen M. Ghogomu, Jacob Souopgui; Methodology, David Beckwee, Cabirou Mounchili Shintouo, Rose Njemini, Lynn Leemans; Project administration Rose Njemini, Tony Mets; Resources, Rose Njemini, David
Funding
This work was supported by VLIR-UOS, Vrije Universiteit Brussel (SGP025 - VLIR358) through the Global Minds Small Great Projects.
Declaration of competing interest
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.
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