| Literature DB >> 34131108 |
Kathrin Cohen Kadosh1, Melissa Basso2, Paul Knytl2, Nicola Johnstone2, Jennifer Y F Lau3, Glenn R Gibson4.
Abstract
The human gut microbiome influence on brain function and mental health is an emerging area of intensive research. Animal and human research indicates adolescence as a sensitive period when the gut-brain axis is fine-tuned, where dietary interventions to change the microbiome may have long-lasting consequences for mental health. This study reports a systematic review and meta-analysis of microbiota-targeted (psychobiotics) interventions on anxiety in youth, with discussion of a consultation on the acceptability of psychobiotic interventions for mental health management amongst youth with lived experience. Six databases were searched for controlled trials in human samples (age range: 10-24 years) seeking to reduce anxiety. Post intervention outcomes were extracted as standard mean differences (SMDs) and pooled based on a random-effects model. 5416 studies were identified: 14 eligible for systematic review and 10 eligible for meta-analysis (total of 324 experimental and 293 control subjects). The meta-analysis found heterogeneity I2 was 12% and the pooled SMD was -0.03 (95% CI: -0.21, 0.14), indicating an absence of effect. One study presented with low bias risk, 5 with high, and 4 with uncertain risk. Accounting for risk, sensitivities analysis revealed a SMD of -0.16 (95% CI: -0.38, 0.07), indicative of minimal efficacy of psychobiotics for anxiety treatment in humans. There is currently limited evidence for use of psychobiotics to treat anxiety in youth. However, future progress will require a multidisciplinary research approach, which gives priority to specifying mechanisms in the human models, providing causal understanding, and addressing the wider context, and would be welcomed by anxious youths.Entities:
Mesh:
Year: 2021 PMID: 34131108 PMCID: PMC8206413 DOI: 10.1038/s41398-021-01422-7
Source DB: PubMed Journal: Transl Psychiatry ISSN: 2158-3188 Impact factor: 6.222
Fig. 1Proposed intervention pathway for the active ingredient.
Adolescence is a time period of ongoing neuro-cognitive development, allowing brain structures and circuities to flexibly adapt- or maladapt to the environment. In this context, gut microbiota might play be a causal role as a mediator between the environment and the CNS via multiple pathways. As easily manipulated throughout diet, it could be a promising and cheap therapy target in the redirection of neurodevelopmental trajectories and improving the mental health outcome for the individual.
Characteristics of the studies included in the systematic review.
| Study | Intervention Type | Delivery Method | Active Compound | Dose | Frequency (dose/day) | Duration (days) | Active/Control | Mean Age (SE) | Sex (M/F) | Anxiety Measure* | Effect | Stress Measure* | Effect2 | Participants |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Andersson et al.[ | probiotic | capsule | 10 x 109 CFU | 1 | 21 | 21/20 | range 18-30 | 13/28 | - | - | salivary cortisol | ↓ | students e.s. | |
| salivary immunoglobulin A | ns | |||||||||||||
| Culpepper et al.[ | probiotic | capsule | 3 × 109 CFU | 1 | 42 | 145 | 19.9 (0.1) | 209/372 | - | - | self-reported stress | ↓ for | students e.s. | |
| 147 | ||||||||||||||
| 142 | ||||||||||||||
| placebo | 147 | |||||||||||||
| Hughes et al. (2011) | prebiotic | sachet | galactooligosaccharide | 0, 2.5, 5 g | 1 | 56 | 279/140 | 19.9 (0.1) | 207/212 | - | - | self-reported stress | ns | students e.s. |
| Karbownik et al.[ | probiotic | capsule | 5 x 109 CFU | 1 | 30 | 31/29 | 22.6 | 37/55 | STAI state | ns | salivary cortisol | ns | students e.s. | |
| salivary metanephrine | ns | |||||||||||||
| pulse rate | ↑ | |||||||||||||
| Kato-Kataoka et al.[ | probiotic | liquid | 100 x 109 CFU | 1 | 56 | 23/24 | 22.8 (0.4) | 25/22 | STAI state | ns | visual analogue stress scale | ↓ | students e.s. | |
| salivary cortisol | ↓ | |||||||||||||
| salivary alpha-amylase | ns | |||||||||||||
| Kato-Kataoka et al.[ | probiotic | liquid | 100 x 109 CFU | 1 | 56 | 24/23 | 22.9 (0.4) | 26/21 | STAI state | ns | salivary cortisol | ns | students e.s. | |
| HADS | - | salivary immunoglobulin A | ns | |||||||||||
| Kitaoka et al.[ | prebiotic | capsule | Fermented Ginseng | 205 mg | 9 | 8 | 8/8 | 20.7 (0.4) | 16/0 | STAI total | - | salivary cortisol | ns | healthy subjects |
| POMS | ns | salivary immunoglobulin A | ns | |||||||||||
| urinary 8-hydroxydeoxyguanosine | ns | |||||||||||||
| Kiecolt-Glaser et al.[ | prebiotic | capsule | omega-3 polyunsaturated fatty acid | 2.5 g | 1 | 84 | 34/34 | 23.7 (1.9) | 38/30 | BAI | ↓ | - | - | students e.s. |
| Liu et al. (2019) | probiotic | capsule | 30 x 109 CFU | ns | 30 | 36/35 | 10.0 | 71/0 | CBCL | ns | - | - | ASD children | |
| Manos et al.[ | prebiotic | capsule | omega-3-PUFA | 782 mg | 4 | 84 | 10/8 | 14.7 | 0/18 | BAIT | ↑ | - | - | anorexic girls |
| Marcos et al.[ | probiotic | liquid | 1 x 109 CFU | 2 | 21 | 73/63 | 18-23 | 40/96 | STAI state | ns | serum cortisol | ns | students e.s. | |
| 10 x 109 CFU | STAI trait | ns | ||||||||||||
| 10 x 109 CFU | ||||||||||||||
| Moller et al. (2017) | probiotic | capsule | 112.5 x 109 CFU (total) | 1 | 14 | 57/48 | 20.2 | 36/69 | - | - | PASAT | ns | healthy subjects, stress task | |
| Blood pressure | ns | |||||||||||||
| Schmidt et al. (2014) | prebiotic | powder | fructooligosaccharides (FOS) | 5.5 g | 1 | 21 | 15 | 23.7 | 22/23 | STAI state | ns | PSS-10 | ns | healthy subjects |
| galactooligosaccharide (B-GOS) | 15 | Attentional dot-probe | ↓GOS only, unmasked | salivary cortisol | ↓ GOS only | |||||||||
| placebo | 15 | Facial expression recognition | ns | |||||||||||
| Emotional word recognition and recall | ns | |||||||||||||
| Tran et al.[ | probiotic | - | 18 species | 50 x 109 CFU | 1 | 28 | 14 | 20.6 | 20/66 | BAI | ns BAI total ↑ BAI-Panic, 50 x 10^9 CFU only | - | - | healthy students |
| 10 species | 50 x 109 CFU | 13 | ACQ-R | - | ||||||||||
| 18 species | 15 x 109 CFU | 15 | PSWQ | ↓50 x 10^9 CFU only | ||||||||||
| 10 species | 10 x 109 CFU | 15 | ||||||||||||
| placebo | 11 |
↓: improvement vs placebo; ↑: deminishment vs placebo; *: effect size estimated or calculated from reported data; ns: no significant effect; -: not reported or not applicable; ACQ-R: Anxiety control questionnaire-revised; BAI: Beck Anxiety Inventory; CBCL: Child Behaviour Checklist (Anxiety); CFU: colony forming units; HADS: Hospital Anxiety and Depression Scale; PASAT: Paced Auditory Serial Addition Test; PSS: Percieved Stress Scale-10; PSWQ: Penn state worry questionnaire; STAI: State-Trait Anxiety Inventory; e.s.: under examination stress.
* all the time point 2 are referred to POST-TREATMENT measurement
Fig. 2PRISMA flowchart of search results at each step of the systematic review.
This illustarates the number of studies considered for inclusion and exclusion throughout the study.
Fig. 3Forest plot of the studies investigating the effect of psychobiotics on anxiety measures.
Fig. 4Forest plot excluding the studies at high risk of bias.
Reasons for high risk are as follows: A Marcos et al. [33]: concerns in regards to the randomization and allocation sequence and non-blinded design; B Kitaoka et al. [39]: unclear anxiety score differences at baseline between the active and control group, absence of a participants flow diagram and of any relevant information about intervention adherence and missing data; C Manos et al. [36]: unclear anxiety score differences at baseline between active (severe anxiety levels) and control (moderate anxiety levels) groups, not specified reasons for no intervention adherence and missing data, no measurement of state anxiety; D Kato-Kataoka et al. [29]: no randomized allocation, significantly different anxiety scores at baseline (p < 0.05) between the active and control group; E Tran et al. [30]: concerns in regard with randomization and allocation process, not enough information about adherence to the intervention and missing data, concerns about the performed statistical analyses.