Differing salivary microbiome diversity, community and diurnal rhythmicity in association with affective state and peripheral inflammation in adults
Introduction
Interactions between gut microbiota and the host play an important role in central nervous system function and behavior, primarily mediated through immune and neuroendocrine pathways (i.e., the gut-brain axis) (Cryan and Dinan, 2012, Liang et al., 2018). Over the past decade, clinical studies and animal models have suggested that chronic distress-related conditions, such as depression and anxiety disorders, are associated with altered gut microbiome composition. For instance, fecal samples from individuals with depression exhibit altered species diversity and taxonomy (Cheung et al., 2019, Horne and Foster, 2018). Various neuropsychiatric conditions are also characterized by under-representation of bacteria that produce anti-inflammatory metabolites (reviewed in Dalile et al., 2019), one potential mechanism by which gut-mediated immune alterations affect behavior. Furthermore, interventions that influence gut-brain interactions may improve depression and anxiety-related symptoms (Bruce-Keller et al., 2018) by altering immune and neuroendocrine pathways, and microbial profiles have been shown to predict treatment responses in mental illness (Mantere et al., 2017).
Our current understanding of these relationships is primarily informed by stool-derived specimens, which, though useful, can be limited by practical sampling issues in certain contexts, such as one or fewer specimens per day based on intestinal motility. By comparison, the oral microbiome (e.g., salivary, supragingival) is relatively straightforward to collect multiple times per day and can be sampled ‘on-demand,’ enabling its investigation in acute laboratory manipulations such as stress reactivity. Although tissue or body-site specific microbiome differences are recognized and such data remain limited, initial reports show modest correlations between oral and gut microbiome composition (Ding and Schloss, 2014, Huttenhower et al., 2012). Oral microbiomes have also been reported to differ in patients with gastrointestinal diseases, such as inflammatory bowel (Said et al., 2014) and celiac disease (Francavilla et al., 2014), as well as inflammatory disorders such as rheumatoid arthritis (Du Teil Espina et al., 2019), and neuropsychiatric disorders, including schizophrenia (Castro-Nallar et al., 2015, Yolken et al., 2015) and Parkinson’s disease (Pereira et al., 2017), as well as obesity (Tam et al., 2018), indicating that diverse pathologies may be reflected in the oral microbiome. What remains unresolved, however, is whether the oral microbiome also serves as a biomarker of subclinical psychological distress or host inflammation, which would provide proof-of-concept for experimental, or observational, investigations of host-microbiome interactions not currently feasible using gut-derived samples.
Studies of the oral microbiome, particularly of saliva, suggest that considerable diurnal variability exists both within and between individuals (Takayasu et al., 2017), similar to the gut (Flores et al., 2014). Part of this variation may be due to host behaviors, such as feeding (Collado et al., 2018) or tooth brushing (Morton et al., 2019). However, emerging evidence suggests that microbiome compositional oscillations may be entrained by and dependent upon host circadian biology (reviewed in Nobs et al., 2019), the disruption of which can affect microbial proliferation and survival. While the mechanisms of circadian cross-talk across physiological systems are poorly understood in the gut or mouth, neuroendocrine and immunological factors impacted by psychological distress may play a role within the oral microenvironment, which could in turn impact oral and/or systemic health. For example, chronic psychological distress, including depressed mood and anxiety, blunts diurnal patterns of glucocorticoid and catecholamine secretion in saliva (e.g., cortisol (Miller et al., 2007) and alpha-amylase (Nater et al., 2007), respectively), both of which are known to modulate gut microbes (Huang et al., 2015, Lyte et al., 2011) and thus, may also blunt diurnal rhythms in relative abundance and/or functional pathways of microbial features within the mouth (Poole et al., 2019).
Chronic distress is also associated with immunosuppression, which can manifest in decreased salivary antibody production (e.g., IgA) (Engeland et al., 2016), an important host factor in oral microbiome homeostasis (reviewed in Bosch et al., 2002). Elevation of proinflammatory cytokines in peripheral blood, such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and interleukin 1-beta (IL-1β), is also observed in chronically distressed individuals (Slavich and Irwin, 2014), and are correlated with salivary cytokine levels during acute psychological stress (La Fratta et al., 2018). Salivary cytokines have been associated with salivary microbial composition in the context of periodontal disease (Lundmark et al., 2019), but relationships with peripheral cytokines in non-clinical samples remain unexplored. However, inter-individual variation in stimulated host cytokine responses is partially explained by gut microbiome composition and may be mediated by immunomodulatory microbial metabolites (Schirmer et al., 2016), which also highlights the need for parallel salivary microbiome data in understanding complex host-microbiome interactions. Little is known about the relationships between the host’s psychological or inflammatory state, salivary microbiome composition, and its diurnal changes.
The present study sought to examine whether salivary microbiome composition was associated with or predictive of distress- and inflammation-derived host profiles in a non-clinical adult population. Furthermore, we hypothesized that individuals with higher distress or inflammation would exhibit altered temporal variability in microbial community structure (e.g., alpha and beta diversity) and less variation in microbial abundance over a single day.
Section snippets
Participants
All participants gave informed consent to the protocol, approved by the University of California, San Diego Institutional Review Board. Data from 68 healthy, non-smoking adults between 20 and 65 years who were recruited from the local community for a larger study of the role of obesity on vascular inflammation and immune cell activation in normotension vs. stage 1 hypertension (SBP: 130–140 mmHg; DBP: 80–90 mmHg), were included in this investigation. Initial screening via telephone interviews,
Psychological and inflammatory characteristics of participants
Psychological characteristics and immune biomarkers for groups are presented in Table 1. As expected, symptoms related to depressed mood, stress, and anxiety were moderately-to-strongly correlated between each other across all subjects (Spearman’s ρ: range = 0.40–0.78; Fig. 1). Similarly, inflammation measures were positively correlated between each other, though somewhat less strongly (ρ: range = 0.16–0.57). Univariate correlations between psychological and inflammatory measures were weak (ρ:
Discussion
In this study, we identified differences in overall composition and diurnal patterns of relative microbial abundance and functional pathways in the salivary microbiome as a function of psychological distress and inflammatory profiles in healthy adults. To our knowledge, this study provides the first evidence that psychological distress and affect in a non-clinical population is associated with greater microbial diversity in saliva, and with specific microbial taxa and functional pathways, and
Acknowledgements
We would like to thank Gregory Humphrey, Lindsay DeRight-Goldasich, Carolina Carpenter, and Tara Schwartz for sample processing, Gail Ackermann for assistance with metadata curation and data handling, and Daniel Freed for his contributions to the project. The authors would like to express their gratitude to all individuals who participated in this study.
Funding Sources
This work was supported by NIH grants R01 HL090975 and HL090975S1 (SH), 1TL1TR001443 (JNK), and a Seed Grant from the UC San Diego Center for Microbiome Innovation (SH).
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