Table 2.
Author/Year | Participants/Sample (Age M ± SD Years) | Sex (M/F) | Study Design | Assessment | Main Findings—Microbiome Link |
---|---|---|---|---|---|
Curtis et al., (2019) [36] | n = 30; non-smokers n = 10 (32 ± 2); eCig users n = 10 (30 ± 3); tobacco smokers n = 10 (37 ± 3) | 28/2 | Cross-sectional group comparison | Resting state functional connectivity of the middle insula; faecal microbiota (16S rRNA) | Insular connectivity is associated with microbiome diversity, structure and at least two specific bacteria genera, potentially modulated by tobacco smoking |
Langgartner et al., (2020) [37] |
n = 40; healthy; rural n = 20 (25.1 ± 0.8); urban n = 20 (24.5 ± 0.8) |
40/0 | Cross-sectional group comparison with stress test | TSST, saliva (oral) microbiota (16S rRNA), IL-6 and cortisol (plasma) and PMBC | No significant difference in alpha or beta diversity (salivary microbiome). Urban upbringing and neg animal contact had effects on salivary microbiome composition linked to stress-induced immune activation. |
Lee et al., (2020) [38] | n = 83 (48.9 ± 13.2) | 37/46 | Correlational; emotional well-being and gut microbiome profiles | Faecal microbiota (16S rRNA), PANAS | Gut microbiome diversity is related to emotional well-being; Prevotella was indicative of positive emotional wellbeing |
Lin et al., (2019) [39] |
n = 60; smokers n = 30 (37.2 ± 9.6); non-smokers n = 30 (37.2 ± 11.8) |
smoker 21/8; non-smoker 20/7 | Cross-sectional group comparison | Resting state fMRI; metagenome inferred from faecal microbiota (16Sr RNA) | Brain functional component differences linked with smoking related microbiota, indicating smoking induced microbiome dysbiosis and brain functional connectivity alteration |
Palomo-Buitrago et al., (2019) [40] |
n = 35; non-obese n = 16 (50.1 ± 10.4); obese n = 19 (53.6 ± 5.9) |
unknown | Cross-sectional group comparison | Faecal microbiota (shotgun) and plasma and faecal glutamate, glutamine and acetate; TMT-A &TMT-B | Slower TMT-A scores associated with relative abundance of Streptococaceae and lower faecal glutamate levels. Corynebacteriaceae and Burkholderiaceae associated with faecal glutamate levels, glutamate/glutamine ratio and faster TMT-A scores |
Taylor et al., (2019) [41] |
n = 133; 25–45 years (33.4 ± 5.8) |
60/73 | Exploratory cross-sectional | DASS- 42; faecal microbiota (16S rRNA); dietary intake and diet quality | Bacterial taxa and DASS relationship. Sex associations with bacterial taxa and DASS, inverse relationship between Anxiety scale scores and Bifidobacterium (females); inverse relationship with Depression scores and Lactobacillus (males). |
Acronyms in order of appearance: mean (M); standard deviation (SD); trier social stress test (TSST); peripheral blood mononuclear cell (PBMC); positive and negative affect schedule (PANAS); functional magnetic resonance imaging (fMRI); trail making test (TMT) A or B; depression, anxiety and stress scale-42 items (DASS-42).