medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Anxiolytic effects of a galacto-oligosaccharides prebiotic in healthy female volunteers 2 are associated with reduced negative bias and the gut bacterial composition.
3
4 Nicola Johnstone1, Chiara Milesi1 , Olivia Burn1 , Bartholomeus van den Bogert2,3, Arjen 5 Nauta4 Kathryn Hart5, Paul Sowden1,6, Philip WJ Burnet7 ,Kathrin Cohen Kadosh1
6 1School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, 7 Guildford, UK 8 2BaseClear, Leiden, The Netherlands 9 3MyMicroZoo, Leiden, The Netherlands 10 4FrieslandCampina, Amersfoort, The Netherlands 11 5Department of Nutritional Sciences, School of Biosciences and Medicine, Faculty of Health 12 and Medical Sciences, University of Surrey, Guildford, UK 13 6Department of Psychology, University of Winchester, Winchester, UK 14 7Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, UK 15
16
17 Corresponding authors
18 Phone: ++44(0) 1483 68 3968
19 Email: [email protected]
20 URL: kcohenkadosh.com
21 Email: [email protected]
22
23 Acknowledgements:
24 This research was supported by faculty research fund from the Faculty of Health and 25 Medical Sciences, University of Surrey, UK to KCK. FrieslandCampina provided the galacto- 26 oligosaccharides (GOS, prebiotics) used in this study.
27 Competing interests
28 AN is an employee of FrieslandCampina.
29 Contributions
30 KCK conceived the study with input from PWJB, PS and KH. CM, OB and NJ acquired the 31 data. NJ and BvdB analysed and interpreted the data. All authors have drafted or 32 substantially revised the article and have approved the present version. All authors agree to 33 be personally accountable in matters relating to their own contributions.
34 Data availability
35 Data and code for reproducible analysis are available at DOI 10.17605/OSF.IO/NGMSU 36
1
NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice. medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Abstract
2 Current research implicates pre- and probiotic supplementation as potential mediators for
3 improving symptomology in numerous physical and emotional ailments. The alteration of
4 emotional states via nutrient intake is an attractive concept for clinicians and consumers
5 alike and may be an efficient channel to improved well-being. Here we focus on the period of
6 late adolescence, which is a time of emotional refinement via maturation that significantly
7 influences emotional, social and physical well-being in later years. Effective interventions
8 such as nutritional supplementation in this age group have the potential to offset health-
9 related costs in later life. In this study we examined multiple indices of mood and well-being
10 in 64 healthy females in late adolescence in a 4-week double blind, placebo controlled
11 Galacto-oligosaccharide (GOS) prebiotic supplement intervention. We also obtained stool
12 samples at baseline and follow-up for microbiome sequencing and analyses. We found
13 effects of the GOS intervention on sub-clinical self-reported high trait anxiety, attentional
14 bias, and bacterial abundance, suggesting that dietary supplementation with a GOS prebiotic
15 may be influential in improving indices of pre-clinical anxiety.
16
2 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Introduction
2 In recent years, the gut microbiome has emerged as an important player in our efforts to
3 understand the factors that influence brain function and behaviour1–4. The gut and the brain
4 are intimately connected via the gut-brain axis, which involves bidirectional communication
5 via neural, endocrine and immune pathways5–7. For example, gut microbial composition —
6 which itself alters throughout the lifespan and in response to factors such as stress and
7 lifestyle choices including diet8 — has been shown to regulate gene expression and the
8 release of metabolites in the brain9,10. There are also suggestions that a significant reduction
9 in microbial diversity, or an increased number of pathogenic microbes, affects brain-
10 behaviour relationships, and may lead to psychological abnormalities that underlie mental
11 illness11. To date, studies in humans have focused on characterising microbe populations in
12 both health and disease4,12. In adults for example, the gut microbiota has been shown to be
13 related to atypical social functioning in autism13 and symptoms of anxiety and depression7,14.
14 Animal research has suggested that the gut microbiota plays an important role during key
15 moments in the host development, and in particular during adolescence which represents a
16 critical time window where microbiota help fine-tune the gut-brain axis3,8,15. One of the
17 consequences gut microbiota variations during neurodevelopment is that it may lead to
18 aberrant brain network maturation and thus atypical behavioural patterns. This supposition
19 highlights the importance of understanding how changes in the gut microbiome relate to
20 brain function and plasticity during this critical developmental period16.
21 Animal research has highlighted the significant impact of the gut microbiota on the
22 development and maturation of brain networks that underlie emotion15–17. Particularly,
23 nutritional interventions have been shown to fortify the microbiome-gut-brain axis and
24 ameliorate microbial imbalances such as dysbiosis. Drastic changes in diet can alter
25 microbial diversity in a matter of days18, and research also suggests that modifying microbial
26 ecology via the intake of so-called ‘psychobiotics’ could help reduce stress responses and
27 symptoms of anxiety and depression19–21. The term psychobiotics refers to live cultures of
3 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 beneficial gut bacteria (probiotics) or substrates which enhance the growth and/or activity of
2 indigenous beneficial intestinal bacteria (prebiotics), which when ingested in sufficient
3 amounts improve brain function22,23. Probiotic strains, including members of the genera
4 Lactobacillus and Bifidobacterium, are enriched in some dairy/fermented products, whereas
5 prebiotics are non-digestible substances that feed the gut microbiome18,24 such as fructans
6 and oligosaccharides found in in cereals, fruits and vegetables22. Both pro- and prebiotic
7 substances are commercially available as supplements. There is no doubt that the
8 administration of psychobiotics (both probiotics and prebiotics) to rodents leads to robust,
9 reproducible, attenuating effects on anxious and depressive-like behaviours, and suppress
10 the neuroendocrine stress response. However, the translatability of these psychotropic
11 actions to humans remains unclear.
12 A recent study in adult volunteers found that the consumption of probiotics in a randomised
13 double-blind trial, reduced measures of low mood and distress, and urinary free cortisol
14 which indicated a decreased stress response25. Similarly, a 4-week course of a multispecies
15 probiotic in healthy participants resulted in reduced responsiveness to sad mood26. A
16 neuroimaging investigation in female participants who had consumed a probiotic containing
17 yoghurt over 4 weeks, revealed differential signals over brain regions involved in emotion
18 processing and regulation27. The main problem of using probiotics is that introducing an
19 allochthonous probiotics species could disturb the cross-feeding microbiota population,
20 which is particularly disruptive in participants with weakened immune systems28. Prebiotics
21 on the other hand support the beneficial bacteria that are already present in the participants’
22 gut, such as Bifidobacterium which have been linked to emotional well-being25–27.
23 Intake of a galacto-oligosaccharides prebiotic over 4 weeks has also been shown to lower
24 the secretion of the stress hormone cortisol and emotional processing in healthy adults29 in
25 comparison to placebo. In the same study, participants exhibited decreased attentional
26 vigilance to negative information in a dot-probe task. Given that anxious people routinely
4 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 exhibit increased biases towards negative information30, this suggests that GOS intake may
2 be useful in modifying anxiety-related psychological mechanisms.
3 The main aim of the current study was to investigate whether GOS intake influences anxiety
4 and mood measures in late adolescence and early adulthood in humans. Specifically, we
5 used emotion regulation as a model for anxiety, as good emotion processing abilities in
6 development are linked with various indices of well-being and mental health31. Moreover, it
7 has been repeatedly shown that adolescence represents an important developmental
8 juncture for both the emergence of social fears31 and the development of emotion control
9 abilities, which allow the individual to control their fear responses and anxiety32. Here we
10 compared the effects of a 4-week course of GOS supplements compared to a placebo on
11 the gut-microbiome and emotional behaviour and well-being. Emotional behaviour was
12 assessed with the attentional dot-probe task29 and a number of self-report measures of
13 anxiety33,34, depression35,36 and emotion regulation abilities37,38. In the current study we
14 hypothesised that daily intake of galacto-oligosaccharides (GOS) for 4 weeks would: 1)
15 reduce self-reported levels of anxiety in the GOS group in comparison to the placebo group;
16 2) improve attentional bias towards positive emotional stimuli in the dot-probe task, and 3)
17 stimulate the fecal abundance of potently beneficial gut bacteria (such as Bifidobacterium) in
18 the GOS compared to the placebo group.
19 Materials and Methods
20 Participants. Sixty-four healthy late adolescent female volunteers were recruited to this
21 double-blind placebo-controlled 4-week galacto-oligosaccharides (GOS) supplement
22 intervention study via posters and online advertisements. Inclusion criteria were no current
23 or previous clinical diagnoses of anxiety or co-morbid neurological, psychiatric,
24 gastrointestinal, or endocrine disorders; no current habitual use of prebiotic or probiotic
25 supplements; no antibiotic use in the 3 months prior to study enrolment and no vegan diets.
26 All participants provided written informed consent prior to testing and received financial
27 compensation for participating in the study.
5 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Participants were screened for trait anxiety scores on the STAI-Trait subscale33 and
2 randomised with stratification for baseline anxiety to either GOS or placebo group based on
3 anxiety level (high or low, median split of sample scores at baseline). This study was given a
4 favourable opinion by the University of Surrey Ethics Committee (UEC/2017/086/FHMS),
5 and is registered on https://www.clinicaltrials.gov number NCT03835468.
6 Design. Power to detect statistically significant effects in behavioural measures was
7 determined to be sufficient with a sample size of 60 participants, posited on small effect
8 sizes found in similar research29. At both testing time points, baseline and follow-up, the
9 same testing protocol was used. Specifically, all participants completed a comprehensive
10 battery of self-report questionnaires (see materials for a description) assessing indices of
11 anxiety33,34, mood35,36, emotion regulation37,38 and sleep39. The self-reported trait anxiety
12 scores at baseline were used to group participants as high or low anxious based on the
13 median score of the sample collected. Participants also completed two subscales (verbal
14 and matrix reasoning) of the Wechsler Abbreviated Scale of Intelligence40 to estimate IQ, as
15 well as the attentional dot-probe task to assess overt emotional processing29. Each
16 participant was also provided with a stool-sampling kit (MyMicroZoo, Leiden, The
17 Netherlands) to self-collect faeces for gut microbiome sequencing analysis. Following the
18 baseline assessment, participants were issued a 28-day supply of supplements (GOS or
19 placebo), which were to be taken once daily. To assess usual intake at the start of the study
20 and to monitor compliance with the dietary instructions (to consume the supplement and to
21 not change their usual diet) participants were also asked to complete a 4-day food estimated
22 diary at each time point which was reviewed by a member of the research team at their
23 testing appointments. The food diary is a semi-quantitative diary used routinely by our group,
24 which required participants to record their intake concurrently during the day in as much
25 detail as possible, including brand names, cooking methods and portion sizes. Diaries were
26 analysed using nutritional analysis software (Nutritics.com) for energy and macro- and
27 micronutrient intakes.
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1 At follow-up, the entire testing protocol was repeated for each participant following cessation
2 of supplement supply (study duration Mdn = 30 days for both GOS group (range: 25-36
3 days) and placebo group (range: 27 - 43 days)), and participants provided a second stool
4 sample.
5 Self-report measures. Participants completed a demographic questionnaire obtaining
6 information on age, height, weight and relevant medical history. Following this, psychological
7 self-assessment questionnaires obtained indices of anxiety, mood and emotion regulation.
8 Anxiety assessments comprised measures of state and trait anxiety (State-Trait Anxiety
9 Inventory; STAI33) and social anxiety (Social Anxiety Scale for Adolescents and Young
10 People; SAS-A34). Mood measures included measures of general mood (Mood and Feelings
11 Questionnaire: Short Version; MFQ36) and depression (Beck Depression Inventory-II; BDI-
12 II35). Emotion regulation was indexed using the Emotion Regulation Questionnaire for
13 Children and Adolescents (ERQ-CA37) and Thought Control Ability Questionnaire (TCAQ38).
14 Finally, participants reported sleep quality for the preceding 1-month period using the
15 Pittsburgh Sleep Quality index (PSQI39).
16 Attentional dot probe task. The attentional dot-probe task was adapted from Schmidt and
17 colleagues29 and presented E-Prime 3.0 software (Psychology Software Tools, Pittsburgh,
18 PA) to assess emotional processing and biases to negative, positive and neutral word pairs
19 in masked and unmasked conditions. Negative and positive words induce emotional bias,
20 whereas neutral word words pairs act as fillers. Masked and unmasked conditions alter
21 awareness of stimulus emotional valence. At the beginning of each trial, a fixation cross
22 appeared on screen for 500 ms. This was followed with a word pair that was one of 30
23 positive-neutral, 30 negative-neutral and 30 neutral-neutral pairs, with words positioned at
24 the top and bottom of the screen. Emotional word position was equally split across top and
25 bottom. In the masked condition (90 trials), word pairs were presented for 17 ms, followed by
26 a length and position matched mask of a nonsense letter string for 483 ms. In the unmasked
27 condition (90 trials), word pairs were presented for 500 ms. This was followed by a probe of
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1 either one or two stars, that was congruent or incongruent with the emotional word position.
2 The participant responded by pressing either ‘1’ or ‘2’ corresponding to the number of stars
3 in the probe, terminating the trial. Frequency of number of stars and of position was equally
4 split across all trials. A total of 180 trials were presented and randomised across masked
5 and unmasked conditions, and valence stimulus pairs. Attentional vigilance was calculated
6 from the response times of correct responses by subtracting congruent RT from incongruent
7 RTs for positive and negative stimuli in masked and unmasked conditions separately. E-
8 Prime 2.0 (Psychology Software Tools, Pittsburgh, PA) was used to present experimental
9 stimuli.
10 GOS/placebo supplement. Participants received either a daily dose of 7 grams of the
11 prebiotic galacto-oliogosaccharides (GOS) provided by FrieslandCampina, Amersfoort, The
12 Netherlands; or a placebo (maltodextrin, dried glucose syrup) for a period of 28 days. GOS
13 are non-digestible carbohydrates, which are not completely broken down by human digestive
14 enzymes. Because of this, they reach the intestine relatively intact, where they are then
15 available for the present microbiota23 whereas Maltodextrin is absorbed in the upper part of
16 the intestine and does not reach the colon. Both supplements were provided in powdered
17 form in unlabelled packaging and are similar in colour and taste. Supplements were
18 instructed to be consumed by mixing with food or drink once daily.
19 Stool sampling. At baseline and follow-up participants were provided with a unique sampling
20 kit provided by MyMicroZoo (Leiden, the Netherlands) for stool collection at home. Feces
21 samples were collected in DNA/RNA Shield (Zymo Research, CA, USA) and returned by the
22 subjects to the recruitment station where collected samples were returned and stored at -
23 80°C prior to being shipped on dry-ice for analysis by MyMicroZoo.
24 DNA extraction. DNA extraction was performed using the Quick-DNA™ Fecal/Soil Microbe
25 Miniprep Kit (Zymo Research) according to manufacturer’s instructions except for using the
26 fecal slurry, containing DNA/RNA Shield, as input during bead beating for mechanical cell
27 lysis instead of using the lysis buffer provided in the extraction kit.
8 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 16S rRNA gene based bacterial profiling. Illumina 16S rRNA gene amplicon libraries were
2 generated and sequenced at BaseClear (Leiden, the Netherlands). In short, barcoded
3 amplicons from the V3-V4 region of 16S rRNA genes were generated using a 2-step PCR.
4 10 genomic (g)DNA was used as template for the first PCR with a total volume of 50 ul using
5 the 341F (5’-CCTACGGGNGGCWGCAG-3’) and the 785R (5’-
6 GACTACHVGGGTATCTAATCC-3’) primers appended with Illumina adaptor sequences.
7 PCR products were purified, and the size of the PCR products were checked on
8 Fragmentanalyzer (Advanced Analytical, CA, USA) and quantified by fluorometric analysis.
9 Purified PCR products were used for the 2nd PCR in combination with sample-specific
10 barcoded primers (Nextera XT index kit; Illumina, CA, Illumina). Subsequently, PCR
11 products were purified, checked on a Fragment analyser and quantified, followed by
12 multiplexing, clustering, and sequencing on an Illumina MiSeq with the paired-end (2x) 300
13 bp protocol and indexing. The sequencing run was analysed with the Illumina CASAVA
14 pipeline (v1.8.3) with demultiplexing based on sample-specific barcodes. The raw
15 sequencing data produced was processed removing the sequence reads of too low quality
16 (only "passing filter" reads were selected) and discarding reads containing adaptor
17 sequences or PhiX control with an in-house filtering protocol. A quality assessment on the
18 remaining reads was performed using the FASTQC quality control tool version 0.10.0. The
19 Illumina paired reads were merged into single reads (so-called pseudoreads) through
20 sequence overlap, after removal of the forward and reverse primers. Chimeric pseudoreads
21 were removed using USEARCH 9.241 and the remaining reads were aligned to the RDP
22 16S rRNA gene database42. Based on the alignment scores of the pseudoreads, the
23 taxonomic depth of the lineage is based on the identity threshold of the rank; Species 99%,
24 Genus 97%, Family 95%, Order 90%, Class 85%, Phylum 80%. Illumina reads were
25 deposited in the European Nucleotide Archive (ENA) database (http://www.ebi.ac.uk/ena) in
26 fastq-format under study accession number PRJEB32693 (or secondary accession number
27 ERP115404). Abundance of each genera was calculated as a percentage of the total
28 number of sequences identified in each sample. Shannon entropy of counts, a metric of
9 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 microbiota diversity, was calculated using USEARCH 9.241 with OTU clustering with a
2 sequencing identity threshold of 97% after subsampling from the entire set, to account for
3 different sampling depths.
4 Multivariate analysis. Partial Redundancy analysis (RDA) was performed using the rda-
5 function in the Vegan-package (version 2.5-443) in R (version 3.3.1) to assess correlations
6 between 16S rRNA gene based bacterial composition data (at the genus level) and the GOS
7 treatment at baseline versus follow-up (as environmental variable), after conditioning the
8 data for the covariate ‘subject’. RDA can be considered a constrained version of Principal
9 Component Analysis (PCA). Where PCA considers all variance encompassed in the data,
10 RDA only considers variance explained by the environmental variables (in this case time,
11 contrasting baseline versus follow-up). The psychological response variables SAS, STAI
12 Trait, STAI state, MFQ, BDI from the self-report measures, and positive and negative bias
13 from attentional vigilance calculations in the dot probe task were fitted onto the ordination. In
14 the resulting biplot, a type 1 (object focused) scaling is employed so that the scores for
15 samples are scaled by eigenvalues and that when plotted, the distances between them
16 represent their similarity (Euclidean distances).
17 Statistical analysis
18 Self-report measures obtained at follow-up were compared using analysis of covariance
19 (ANCOVAs) between intervention groups (GOS and placebo) and anxiety grouping (High
20 and Low) considering baseline measures as a covariate. Baseline measures were initially
21 tested for differences between intervention groups prior to using ANCOVAs. Similarly,
22 attentional dot-probe outcomes at follow-up were assessed for attentional vigilance to
23 positive and negative stimuli in the masked and unmasked conditions using ANCOVAs
24 between intervention and anxiety groups with baseline measures as a covariate. Bacterial
25 diversity at follow up was also evaluated with ANCOVA examining intervention and anxiety
26 groups. Bacterial abundance of all genera was evaluated using non-parametric calculations
27 comparing intervention groups at baseline and follow-up (Wilcoxon rank-sum test for
10 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 independent groups), and each intervention group across time (Wilcoxon signed rank test for
2 paired samples). Unrestricted Permutation Test was used to assess significance of the GOS
3 treatment and was indicated in the RDA diagrams. Statistical testing was performed in R
4 (version 3.5.144).
5 Results
6 A 25% attrition rate resulted in 48 participants completing the study, n = 23 in the GOS
7 group (high anxiety n = 12, low anxiety n = 11) and n = 25 in the placebo group (high anxiety
8 n = 13, low anxiety n = 12), matched for age (GOS median (Mdn) = 19 years (range: 18-25),
9 placebo Mdn = 20 years (range: 18-25)), IQ (GOS Mdn = 103 (83-148), placebo Mdn = 102
10 (72-125)) and BMI (GOS Mdn = 20.5 kg/m2 (range: 18.8-30.1), placebo = Mdn 20.3 kg/m2
11 (range: 16.2 – 27.2)). Diets were consistent across time for each supplement group for total
12 energy consumption, although the GOS group had lower overall energy intake than placebo
13 at both baseline (p = .009) and follow up (p = .025). At the macro level, consumption was
14 estimated as a percentage of energy intake for each individual over the first (baseline) and
15 last (follow up) four-day period of supplement intake. Between GOS and placebo groups,
16 non-parametric tests showed no significant difference for carbohydrate, fat, protein, dietary
17 saturated fat, sugars or alcohol intake. From baseline to follow up paired sample non-
18 parametric tests showed no difference in any of the aforementioned measures in the placebo
19 group, but the GOS group demonstrated a reduction in sugar consumption at follow up (p =
20 .010), with all other measures remaining consistent (Supplementary table 1).
21 Self-report measures. For all measures, models comparing baseline scores confirmed no
22 differences between groups thus ANCOVA was used to compare group means at follow-up
23 (Table 1). The significant interaction of intervention and anxiety grouping on trait anxiety
24 scores F(1,42) = 5.58, p = .023, n2 = .03 was followed up with further ANCOVAs examining
25 the influence of intervention for anxiety grouping independently. It was found that compared
26 to the placebo group, four weeks of GOS consumption reduced self-reported scores for high
2 27 anxious participants at trend-level F(1,21) = 3.88, p = .062, n = .12; adjusted means GOS M
11 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 = 45.47, SE = 1.43 [CI 42.49 – 48.43]; placebo M = 49.45, SE = 1.43 [CI 46.48 – 52.42] but
2 not for the low anxious group F(1,20) = 1.84, p = .190, GOS M = 32.34, SE = 1.59 [CI 29.03
3 – 35.65]; Placebo M = 29.36, SE = 1.52 [CI 26.19 – 32.52] (Figure 1). There were no other
4 interactions between intervention group and anxiety group for social or state anxiety, or in
5 mood measures (BDI or MFQ), emotion regulation or sleep quality index (Supplementary
6 Table 2).
7 Table 1. Self-report measure adjusted means at follow-up with ANCOVA interaction
Intervention: Anxiety High Low Interaction M (SE) M (SE) P Anxiety Trait (STAI)45 GOS 41.57 (1.81) 36.41 (1.88) Placebo 45.56 (1.80) 33.42 (1.83) 0.023 State (STAI)45 GOS 37.23 (1.90) 29.54 (2.07) Placebo 34.08 (2.02) 31.40 (2.02) 0.181 SAS-A 44 GOS 44.17 (1.88) 44.72 (1.98) Placebo 45.40 (1.77) 42.74 (1.84) 0.377 Mood MFQ42 GOS 5.75 (1.01) 3.38 (1.09) Placebo 6.09 (1.07) 2.31 (1.08) 0.475 BDI-II 43 GOS 9.46 (1.30) 7.88 (1.40) Placebo 9.07 (1.38) 5.07 (1.39) 0.354 Emotion Regulation Reappraisal (ERQ-CA)49 GOS 20.72 (.090) 21.10 (0.93) Placebo 20.22 (0.86) 22.62 (0.90) 0.264 Suppression (ERQ-CA)49 GOS 11.57 (0.79) 11.44 (0.83) Placebo 10.85 (0.76) 10.11 (0.79) 0.703 TCAQ 50 GOS 77.92 (2.54) 86.33 (2.79) Placebo 73.60 (2.61) 85.79 (2.63) 0.434 Sleep PSQI47 GOS 5.43 (0.63) 4.71 (0.68) Placebo 5.95 (0.64) 4.81 (0.63) 0.749
12 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1
2 Figure 1. Trait anxiety scores at follow-up (plotted as z-scores, error bars are SE). Scores
3 are reduced in the high anxious (x-axis) GOS group compared to the high anxious placebo
4 group. * p = .062.
5
6
7 Attentional Dot Probe task. An initial model found no group differences at baseline again
8 confirming suitability of ANCOVA. An interaction of block (masked and unmasked),
9 emotional valence (positive and negative), intervention group (GOS and placebo) and
10 anxiety group (high and low) was found F(1,175) = 4.26, p = .04, n2 = .022. This interaction
11 was then modelled by block separately. There was no significant interaction in the masked
12 block, F(1,87) = 0.07, p = .788; however, there was a significant interaction with emotional
13 valence, intervention group and anxiety group in the unmasked block, F(1,87) = 7.10, p =
14 .009, n2 = .073. This was further modelled by anxiety grouping independently to examine the
15 influence of intervention group on emotional valance stimuli (Figure 2). In the high anxious
16 group, there was a trend towards an interaction between intervention group and valence
17 condition, F(1,45) = 3.46, p = .070, n2 = .071, where participants in the GOS group in
18 comparison to the placebo group showed reduced bias to negative stimuli, GOS M = -34.86
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1 ms, SE = 18.86 [CI -72.86 – 3.13]; Placebo M = 3.67 ms, SE = 18.18 [CI -32.95 – 40.29];
2 and greater bias to positive stimuli, GOS M = 3.62 ms, SE = 18.90 [CI -34.45 – 41.69];
3 Placebo M = -26.36 ms, SE = 18.09 [CI -62.82 – 10.08]. The trend towards interaction
4 between intervention group and valence condition was also found in the low anxious group,
5 F(1,41) = 3.49, p = .069, n2 = .073. Unlike in the high anxious participants, the low anxious
6 placebo group in comparison to the GOS group demonstrated decreased bias to negative
7 stimuli GOS M = 2.28 ms, SE = 20.07 [CI -38.26 – 42.83]; Placebo M = -24.15 ms, SE =
8 19.29 [CI -63.11 – 14.80]; and increased bias to positive stimuli, GOS M = -14.63 ms, SE =
9 20.34 [CI -55.73 – 26.45]; Placebo M = 31.81 ms, SE = 19.33 [CI -63.11 – 14.80].
10
11 Figure 2. Interaction of attentional vigilance to stimulus valence (y-axis, bias score (z-
12 scores)) by intervention group in the high anxious group, and the low anxious group at
13 follow-up. Error bars illustrate SE A, In high anxious group, GOS group participants show a
14 trend towards reduced bias to negative stimuli, and increased bias to positive stimuli in
15 comparison to the placebo group. B, in low anxious group the placebo group show a trend
16 towards reduced bias to negative stimuli, and increased bias to positive stimuli in
17 comparison to the GOS group.
14 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1
2 Bacterial composition analysis. Descriptive means of bacterial diversity are displayed in
3 supplementary Table 3. There were no changes in diversity due to intervention or anxiety
4 grouping at follow up as illustrated in the ANCOVA results. There was no main effect of
5 intervention group (F(1,43) = 2.08, p = .15, n2 = .04), anxiety group (F(1,43) = 2.63, p = .11,
6 n2 = .05), or interaction of intervention and anxiety group (F(1,43) = 0.01, p = .89, n2 < .01).
7 All genera identified in the microbiome were also evaluated using paired non-parametric
8 comparisons within each intervention group from baseline to follow-up, and independent
9 non-parametric comparisons between intervention groups at baseline and follow-up.
10 Within group measures. Table 2 displays the significant differences from baseline to
11 follow-up for both GOS and placebo groups. Only Bifidobacterium was found have significant
12 changes in abundance greater than 1%, and only in the GOS group; baseline, M = 6.1, SE =
13 1.6, follow-up, M = 9.6, SE = 2.0; p = 0.032 illustrating a 3.49% increase. There was no
14 change in Bifidobacterium abundance in the placebo group; baseline, M = 8.2, SE = 2.1,
15 follow-up, M = 8.0, SE = 1.4; p = 0.989 (Figure 3). Other significant changes across time in
16 genera abundances in the GOS group (supplementary Figure 1) were substantially lower;
17 abundances of the bacteria groups unclassified Streptococcaceae, Falcatimonas,
18 Lachnoanaerobaculum, Lachnospira decreased in the GOS group, while the abundances of
19 Faecalicoccus increased. In the placebo group other changes were observed (Table 2) for
20 low abundant members of the phylum of Proteobacteria there was an increase in specific
21 pathogens (e.g. Escherichia, Salmonella, and Shigella). Notably, the abundances of these
22 groups were not found to be significantly different for subjects in the GOS group
23 (supplementary Figure 2).
15
medRxiv preprint was notcertifiedbypeerreview)
1 Table 2. Significant differences in microbial bacteria abundance within GOS and placebo groups from baseline to follow-up. Arrows
2 show direction of effect. doi: https://doi.org/10.1101/19011403
Placebo GOS Difference Difference Class Order Family Genus Mean (%) p Mean (%) p It ismadeavailableundera Phylum: Actinobacteria
istheauthor/funder,whohasgrantedmedRxivalicensetodisplaypreprintinperpetuity. Actinobacteria Bifidobacteriales Bifidobacteriaceae Bifidobacterium -0.273 .989 ↑ 3.490 .032 Actinobacteria Bifidobacteriales Bifidobacteriaceae Gardnerella ↑ 0.046 .009 0.001 .100 Coriobacteriia Eggerthellales Eggerthellaceae Eggerthella ↑ 0.038 .047 -0.005 .697 Phylum: Firmicutes ;
this versionpostedDecember4,2019. Bacilli Lactobacillales Streptococcaceae unclassified Streptococcaceae 0.001 .485 ↓ -0.003 .018
Clostridia Clostridiales Clostridiaceae Falcatimonas -0.003 .786 -0.036 .007 CC-BY-NC-ND 4.0Internationallicense Clostridia Clostridiales Eubacteriaceae unclassified Eubacteriaceae ↑ 0.039 .013 0.008 .651 Clostridia Clostridiales Lachnospiraceae Lachnoanaerobaculum 0.003 .764 ↓ -0.021 .020 Clostridia Clostridiales Lachnospiraceae Lachnospira -0.035 .558 ↓ -0.042 .040 Clostridia Clostridiales Lachnospiraceae Oribacterium ↓ -0.008 .047 -0.002 .897 Clostridia Clostridiales Lachnospiraceae Pseudobutyrivibrio ↓ -0.009 .015 -0.002 .728 Clostridia Clostridiales Ruminococcaceae Ethanoligenens ↑ 0.005 .032 0.006 .925 Clostridia Clostridiales Ruminococcaceae Ruminiclostridium ↑ 0.355 .005 -0.110 .673 Clostridia Clostridiales Ruminococcaceae Ruminococcus ↑ 1.300 .044 -1.193 .436 Clostridia Clostridiales Ruminococcaceae Ruthenibacterium ↑ 0.119 .047 0.010 .444 Clostridia Clostridiales Ruminococcaceae Saccharofermentans ↑ 0.084 .050 -0.006 .965 The copyrightholderforthispreprint Erysipelotrichia Erysipelotrichales Erysipelotrichaceae Faecalicoccus 0.006 .317 ↑ 0.022 .018 Phylum: Proteobacteria .
Alpha- proteobacteria Rhodospirillales Rhodospirillaceae Rhodospirillum ↑ 0.001 .032 0.001 .205 Gamma- proteobacteria Enterobacterales Enterobacteriaceae Escherichia ↑ 0.670 .040 0.623 .154 Gamma- proteobacteria Enterobacterales Enterobacteriaceae Kosakonia ↑ 0.006 .044 0.007 .126 Gamma- Enterobacterales Enterobacteriaceae Salmonella ↑ 0.004 .009 0.002 .205
16 (which
medRxiv preprint was notcertifiedbypeerreview)
Proteobacteria Gamma- proteobacteria Enterobacterales Enterobacteriaceae Shigella ↑ 0.016 .021 0.014 .410 doi:
https://doi.org/10.1101/19011403 It ismadeavailableundera istheauthor/funder,whohasgrantedmedRxivalicensetodisplaypreprintinperpetuity. ; this versionpostedDecember4,2019. CC-BY-NC-ND 4.0Internationallicense The copyrightholderforthispreprint .
17 (which medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1
Figure 3. A Comparison of Bifidobacterium abundance at baseline and follow up for both intervention groups. Boxplots enclose data within the 25th-75th percentiles with whiskers a maximum of 1.5 times the distance of box range. Median is indicated by horizontal line, and individual data plotted. There is a significant increase in Bifidobacterium in the GOS group at follow up compared to baseline * p = .036. B. Change in Bifidobacterium abundance for high and low anxious participants in each intervention group from baseline to follow up. Dots represent individual participants. Those above the zero axis illustrate an increase in the abundance of Bifidobacterium at follow up, those below a decrease. 2
3 Between group measures. Between group differences at baseline and follow-up are
4 displayed in Table 3, with no genera surpassing a difference in abundance across groups of
5 more than 1%, including Bifidobacterium (baseline, p = 0.20 or follow-up, p = 0.69). At
6 baseline, there were few significant differences between intervention groups (supplementary
7 Figure 3). For the genus Dorea, Catonella, Peptococcus and Holdemania initial abundances
8 were significantly lower in the GOS group in comparison to the placebo group. Bacterial
9 abundances for the genera Turicibacter and Kosakonia at the baseline samples from the
10 placebo group were lower than in the GOS group. At follow-up, again there are few between
11 group differences, with genera identified in each phylum of Bacteroidetes, Actinobacteria
18 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 and Firmicutes (supplementary Figure 4) showing decreased abundance in the GOS group
2 compared with the placebo group, with little relation easily identified between the specific
3 genera.
19
medRxiv preprint was notcertifiedbypeerreview)
1 Table 3. Significant differences between GOS and placebo group at baseline and follow-up. Difference means are calculated in
2 reference to placebo group and arrows show direction of effect. doi: https://doi.org/10.1101/19011403
Baseline Follow-up Difference Difference Class Order Family Genus p p
Mean (%) Mean (%) It ismadeavailableundera Phylum: Actinobacteria
istheauthor/funder,whohasgrantedmedRxivalicensetodisplaypreprintinperpetuity. Actinobacteria Actinomycetales Actinomycetaceae Actinomyces 0.106 ↓ 0.044 -0.0001 0.020 Coriobacteriia Coriobacteriales Atopobiaceae Atopobium 0.484 ↓ 0.033 -0.002 0.001 Phylum: Bacteroidetes
; this versionpostedDecember4,2019. Bacteroidia Bacteroidales Prevotellaceae Prevotella 0.912 ↑ 0.019 0.765 -0.271 Sphingobacteriia Sphingobacteriales Sphingobacteriaceae Sphingobacterium 0.79 ↓ 0.047 -0.003 0.007 CC-BY-NC-ND 4.0Internationallicense Phylum: Firmicutes
Bacilli Bacillales Staphylococcaceae Staphylococcus 0.435 ↓ 0.017 0.002 0.004 unclassified Bacilli Lactobacillales Streptococcaceae 0.355 0.031 Streptococcaceae -0.001 ↓ 0.003 Clostridia Clostridiales Clostridiaceae Lactonifactor 0.766 ↓ 0.019 0.002 0.015 Clostridia Clostridiales Clostridiales Family XIII. Mogibacterium 0.18 ↓ 0.007 -0.010 0.018 Clostridia Clostridiales Lachnospiraceae Dorea ↓ 0.335 0.028 0.588 0.002
Clostridia Clostridiales Lachnospiraceae Eisenbergiella 0.137 ↓ 0.025 The copyrightholderforthispreprint 0.039 0.053 Clostridia Clostridiales Lachnospiraceae Catonella ↓ 0.002 0.028 0.001 0.68
Clostridia Clostridiales Peptococcaceae Peptococcus ↓ 0.014 0.008 0.005 0.234 . Erysipelotrichia Erysipelotrichales Erysipelotrichaceae Holdemania ↓ 0.022 0.014 0.004 0.434 Erysipelotrichia Erysipelotrichales Erysipelotrichaceae Turicibacter 0.032 0.344 -0.185 -0.002 Phylum: Proteobacteria
Gamma- Enterobacterales Enterobacteriaceae Kosakonia proteobacteria ↑ -0.006 0.028 -0.006 0.154 3
20 (which medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 RDA analysis. RDA analysis was performed for both the GOS and placebo group and
2 anxiety group separately contrasting measures across time from baseline to follow-up.
3 Results are displayed in the ordination diagrams in Figure 4. For individuals in the GOS
4 group classified as ‘high anxious’ at baseline, genus level microbiota communities showed a
5 trend level difference at follow-up, albeit with a low significance (p = .088). For the GOS low
6 anxious group, there was no significant prediction of microbiome genera on psychological
7 measures across time p = .414. In the placebo groups, the low anxious participants illustrate
8 trending effects towards differential microbiota communities from baseline to follow up (p =
9 .103) similar to the high anxious GOS participants. There was no such effect in the high
10 anxious participants, p = .419.
21 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1
2 Figure 4. Ordination diagram from RDA for samples from the placebo and GOS group
3 collected at baseline and follow-up, where the RDA indicates the association between Time
4 (explanatory variables (x axis)) and bacterial community data on the Genus level. Scores of
5 the first RDA-axis are plotted on the x-axis and scores of the first PCA-axis are plotted on
6 the y-axis. Individual samples are represented by points that are coloured by time and
7 samples belonging to the same collection time are enveloped. Triangles in the RDA
8 diagrams represent the class centroids. Grey points and labels represent the 10 best-fitting
9 genus level bacterial groups. The psychological measurements (environmental variables)
10 are fitted onto the ordination and indicated by the named arrows. The arrow shows the
22 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 direction of the (increasing) gradient, and the length of the arrow is proportional to the
2 correlation between the variable and the ordination. Only those psychological measurements
3 with a p value of <0.10 are added to the ordination. The calculated p-value from Unrestricted
4 Permutation Test is added to the upper left corner of the RDA diagram.
5
23 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Discussion
2 In this double-blind placebo-controlled 4-week galacto-oligosaccharides (GOS) supplement
3 intervention study we sought to characterise the influence of GOS on indices of emotional
4 well-being and microbial gut composition in a sample of female participants towards the end
5 of adolescence. We found anxiolytic effects of GOS in high anxious participants in self-
6 reported trait anxiety and trends towards reduced negative emotional bias and increased
7 positive bias in the dot-probe task. Additionally, microbial composition was characterised by
8 increased Bifidobacterium abundances at follow up in the GOS group. RDA analysis of
9 microbial composition against psychological measures found trend level separation of
10 bacterial composition in high anxious females at follow up compared to baseline. Altogether,
11 these data indicate that GOS supplementation raises fecal abundances of Bifidobacterium
12 and has an anxiolytic influence on emotional wellbeing in high anxious late adolescent
13 females.
14 The anxiolytic effects evident in this intervention are in line with a prior community study of
15 GOS whereby stress indicators were reduced and emotional behaviour improved following 3
16 weeks of GOS supplementation29, adding corroborative evidence to the literature that GOS
17 supplementation assists in functional enhancement of biological networks underpinning
18 emotion regulation and mood. Anxiolytic and antidepressant effects of multispec pre- and
19 probiotics are apparent in several in-human studies e.g. 25–27,29,45, however, results of this
20 study elucidated no demonstrable impact of GOS on measures of mood, depression,
21 emotion regulation or indeed social or state reported anxiety levels. Some clinical trials have
22 linked pro- or prebiotic intake to reduced depression26 or anxiety46,47, others have found no
23 support48–50. In these trials, measures of depression and anxiety are usually secondary to
24 primary outcomes in overall improvement in clinical conditions51 and are comorbid in the
25 function of existing dysregulated biological systems (e.g. IBS46,47, rheumatoid arthritis52,
26 fibromyalgia48). The finding that GOS only impacts self-reported sub-clinical trait anxiety in
24 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 this study suggests a dimension of sensitivity in late adolescent females that would benefit
2 from further exploration.
3 Trait anxiety is a persistent emotional state characterised by doubts, fear and worry. When
4 such a state co-occurs with the final period of maturation in late adolescents, emotion
5 regulation ability is key for determining the trajectory for lifelong behaviours53. Animal models
6 have shown that dysbiosis in adolescence results in lasting effects on brain-behaviour
7 interactions8,15. While gut-microbiota-brain (GMB) influences are bidirectional, biological
8 systems may be fine-tuned via nutritional intake. This may benefit late adolescence females,
9 especially those subject to transient suboptimal emotional regulation skills in the final stages
10 of maturation (e.g. displaying symptoms of stress and anxiety). Nutritional supplementation
11 and consequential influence on GMB may prove effective in stabilising some of these
12 symptoms in this age group. Probiotics are known to influence the gut-brain axis via
13 endocrine, immune and neural pathways27,54,55. For example, Lactobacillus rhamnosus
14 intake exerts influence on GABA receptors in the brain54, which cooperates with excitatory
15 glutamate to regulate brain function. Glutamate and GABA are respectively excitatory and
16 inhibitory neurotransmitters that are essential in typical cognitive development56. In anxious
17 individuals, disruption to the balance of this relationship is correlated with poorer cognitive
18 control57 and influences emotion regulation ability. The intake of pre- and probiotics may
19 contribute to the harmonisation of the excitatory/inhibitory balance.
20 We affirmed a clear influence of GOS intake on Bifidobacterium increase across time in
21 comparison to placebo group. Data are also suggestive of a decrease in potential
22 pathogens. While measures of microbiota diversity are similar across groups and time, it
23 may be that GOS intake resulted in the prevention of potentially unhealthy bacteria, offering
24 protective benefits. Admittedly, it is difficult to disentangle if the influence of GOS observed
25 in these data is due to the stimulation of Bifidobacterium growth, or the reduction in
26 proteobacteria. Naturally, diet is likely a key component of this relationship and in this
27 sample, we found little support for dietary changes in groups across time, excepting reduced
25 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 sugar intake in the GOS group, or between groups. This strengthens the hypothesis that
2 GOS exerts beneficial influence on well-being, yet the mechanisms of this require further
3 investigation. Regardless, the subtle fine tuning of microbiota with GOS intake may be
4 enough to assist in the biological regulation of emotional pathways and contribute to
5 improved well-being in pre-clinical populations.
6 Of note in the outcome of this study is the relatively small effect sizes and trend level p-
7 values of our self-report psychological measures and dot probe task. The dot-probe task
8 encapsulates attentional biases to emotional stimuli. Prevalent, heightened anxiety
9 commonly results in attentional bias to negative, or threating information30, and can be
10 reduced by attentional bias modification training58. Attentional training works to modify
11 emotion regulation networks in the brain59 however, there are questions surrounding the
12 consistency of the manifestation of attentional biases at the individual level59. In the absence
13 of attentional bias training, results from the dot probe task were indicative of trends towards
14 reduced negative bias and increased positive bias to emotional stimuli in the high anxious
15 GOS group, a pattern that was also observed in the low-anxious placebo group. While this
16 may indicate that high anxious GOS participants have undergone alterations in cognitive-
17 emotional processing compared to the high anxious placebo group, it is difficult to cleanly
18 interpret as the low anxious GOS group results do not mirror their placebo counterparts.
19 Although there are trends towards interventional effects, individual variability in anxiety
20 expression within intervention groups may be influenced by variables not accounted for in
21 this study.
22 Similar community sample research produce equally small effect sizes on comparative
23 measures29. This might be anticipated in an intervention in sub-clinical typical populations
24 examining factors at group level where specific pathways and mechanisms are yet to be fully
25 established. Well defined operational measures with strong correlations to mediating
26 pathways as exhibited in animal studies may result in more targeted therapeutic potential of
27 GOS in humans. Herein, GOS has been established to increase Bifidobacterium abundance
26 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 in 4 weeks in co-occurrence with reduced anxiety manifestation, with indications of
2 modification of attentional bias in a sample of adolescent females. Data presented here are
3 indicative that GOS may be effective in influencing the expression of anxiety and would
4 benefit from further research specifying potential pathways of this effect.
5
27 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 References
2 1. Tang, F., Reddy, B. L. & Saier Jr., M. H. Psychobiotics and Their Involvement in
3 Mental Health. J. Mol. Microbiol. Biotechnol. 24, 211–214 (2014).
4 2. Sarkar, A. et al. Psychobiotics and the Manipulation of Bacteria-Gut-Brain Signals.
5 Trends Neurosci. 39, 763–781 (2016).
6 3. McVey Neufeld, K.-A., Luczynski, P., Seira Oriach, C., Dinan, T. G. & Cryan, J. F.
7 What’s bugging your teen?—The microbiota and adolescent mental health. Neurosci.
8 Biobehav. Rev. 70, 300–312 (2016).
9 4. Consortium, T. H. M. P. et al. A framework for human microbiome research. Nature
10 486, 215–221 (2012).
11 5. Grenham, S., Clarke, G., Cryan, J. F. & Dinan, T. G. Brain-gut-microbe
12 communication in health and disease. Front. Physiol. 2 DEC, 94 (2011).
13 6. Grossman, M. I. Neural and Hormonal Regulation of Gastrointestinal Function: An
14 Overview. Annu. Rev. Physiol. 41, 27–27 (2003).
15 7. Mayer, E. A., Knight, R., Mazmanian, S. K., Cryan, J. F. & Tillisch, K. Gut Microbes
16 and the Brain: Paradigm Shift in Neuroscience. J. Neurosci. 34, 15490–15496 (2014).
17 8. Turnbaugh, P. J. et al. The effect of diet on the human gut microbiome: A
18 metagenomic analysis in humanized gnotobiotic mice. Sci. Transl. Med. 1, 6ra14-
19 6ra14 (2009).
20 9. Oldham, M. C. et al. Functional organisation of the transcriptome in human brain. 11,
21 (2008).
22 10. Desbonnet, L., Garrett, L., Clarke, G., Bienenstock, J. & Dinan, T. G. The probiotic
23 Bifidobacteria infantis: An assessment of potential antidepressant properties in the rat.
24 J. Psychiatr. Res. 43, 164–174 (2008).
28 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 11. Foster, J. A. & McVey Neufeld, K.-A. Gut–brain axis: how the microbiome influences
2 anxiety and depression. Trends Neurosci. 36, 305–312 (2013).
3 12. Lloyd-Price, J. et al. Strains, functions and dynamics in the expanded Human
4 Microbiome Project. Nature 550, 61–66 (2017).
5 13. Mccartney, A. L., Parracho, H. M. R. T., Bingham, M. O. & Gibson, G. R. Differences
6 between the gut microflora of children with autistic spectrum disorders and that of
7 healthy children. J. Med. Microbiol. 54, 987–991 (2005).
8 14. Mayer, E. A. Gut feelings: the emerging biology of gut–brain communication. Nat.
9 Rev. Neurosci. 12, 453–466 (2011).
10 15. Stilling, R. M. et al. Microbes & neurodevelopment – Absence of microbiota during
11 early life increases activity-related transcriptional pathways in the amygdala. Brain.
12 Behav. Immun. 50, 209–220 (2015).
13 16. Chen, J. et al. Effects of gut microbiota on the microRNA and mRNA expression in the
14 hippocampus of mice. Behav. Brain Res. 322, 34–41 (2017).
15 17. Diaz Heijtz, R. et al. Normal gut microbiota modulates brain development and
16 behavior. Proc. Natl. Acad. Sci. U. S. A. 108, 3047–52 (2011).
17 18. David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome.
18 Nature 505, 559–63 (2014).
19 19. Bindels, L. B., Delzenne, N. M., Cani, P. D. & Walter, J. Towards a more
20 comprehensive concept for prebiotics. Nat. Rev. Gastroenterol. Hepatol. 12, 303–310
21 (2015).
22 20. Dinan, T. G., Stanton, C. & Cryan, J. F. Psychobiotics: a novel class of psychotropic.
23 Biol. Psychiatry 74, 720–6 (2013).
24 21. Burnet, P. W. J. & Cowen, P. J. Psychobiotics highlight the pathways to happiness.
29 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Biol. Psychiatry 74, 708–9 (2013).
2 22. Boehm, G. et al. Prebiotics in Infant Formulas. J. Clin. Gastroenterol. 38, S76–S79
3 (2004).
4 23. Gibson, G. R. et al. Dietary prebiotics: current status and new definition. (2010).
5 24. Barile, D. & Rastall, R. A. Human milk and related oligosaccharides as prebiotics.
6 Current Opinion in Biotechnology 24, 214–219 (2013).
7 25. Messaoudi, M. et al. Beneficial psychological effects of a probiotic formulation (
8 Lactobacillus helveticus R0052 and Bifidobacterium longum R0175) in healthy human
9 volunteers. Gut Microbes 2, 256–261 (2011).
10 26. Steenbergen, L., Sellaro, R., van Hemert, S., Bosch, J. A. & Colzato, L. S. A
11 randomized controlled trial to test the effect of multispecies probiotics on cognitive
12 reactivity to sad mood. Brain. Behav. Immun. 48, 258–264 (2015).
13 27. Tillisch, K. et al. Consumption of Fermented Milk Product With Probiotic Modulates
14 Brain Activity. Gastroenterology 144, 1394-1401.e4 (2013).
15 28. Zmora, N. et al. Personalized Gut Mucosal Colonization Resistance to Empiric
16 Probiotics Is Associated with Unique Host and Microbiome Features. Cell 174, 1388-
17 1405.e21 (2018).
18 29. Schmidt, K. et al. Prebiotic intake reduces the waking cortisol response and alters
19 emotional bias in healthy volunteers. Psychopharmacology (Berl). 232, 1793–801
20 (2015).
21 30. Bar-Haim, Y., Lamy, D., Pergamin, L., Bakermans-Kranenburg, M. J. & van
22 IJzendoorn, M. H. Threat-related attentional bias in anxious and nonanxious
23 individuals: A meta-analytic study. Psychol. Bull. 133, 1–24 (2007).
24 31. Kessler, R. C. et al. Lifetime prevalence and age-of-onset distributions of DSM-IV
30 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 disorders in the national comorbidity survey replication. Archives of General
2 Psychiatry 62, 593–602 (2005).
3 32. Trentacosta, C. J. & Fine, S. E. Emotion Knowledge, Social Competence, and
4 Behavior Problems in Childhood and Adolescence: A Meta-analytic Review. Soc.
5 Dev. 19, 1–29 (2010).
6 33. Spielberger, C. D., Gorsuch, R. L., Lushene, R., Vagg, P. R. & Jacobs, G. A. State-
7 Trait Anxiety Inventory for Adults. (Mind Garden Inc., 1983).
8 34. La Greca, A. M. Manual for the Social Anxiety Scales for Children and Adolescents -
9 Revised. (University of Miami, 1999).
10 35. Beck, A. T., Steer, R. A. & Brown, G. K. BDI-II: Beck Depression Inventory Manual.
11 (Psychological Corporation, 1996).
12 36. Angold, A. et al. Development of a short questionnaire for use in epidemiological
13 studies of depression in children and asolescents. J. Methods Psychiatr. Res. 5, 237–
14 249 (1995).
15 37. Gullone, E. & Taffe, J. The Emotion Regulation Questionnaire for Children and
16 Adolescents (ERQ–CA): A psychometric evaluation. Psychol. Assess. 24, 409–417
17 (2012).
18 38. Luciano, J. V., Algarabel, S., Tomás, J. M. & Martínez, J. L. Development and
19 validation of the thought control ability questionnaire. Pers. Individ. Dif. 38, 997–1008
20 (2004).
21 39. Buysse, D. J., Reynolds, C. F., Monk, T. H., Berman, S. R. & Kupfer, D. J. The
22 Pittsburgh sleep quality index: A new instrument for psychiatric practice and research.
23 Psychiatry Res. 28, 193–213 (1989).
24 40. Wechsler, D. Wechsler Abbreviated Scale of Intelligence. (The Psychological
25 Corporation, 1999).
31 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 41. Edgar, R. C. Search and clustering orders of magnitude faster than BLAST.
2 Bioinformatics 26, 2460–2461 (2010).
3 42. Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian Classifier for
4 Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy. Appl.
5 Environ. Microbiol. 73, 5261–5267 (2007).
6 43. Oksanen, J. et al. vegan: Community Ecology Package. (2019).
7 44. Team, R. C. R: A language and environment for statistical computing. R Foundation
8 for Statistical Computing. (2018).
9 45. Luo, J. et al. Ingestion of Lactobacillus strain reduces anxiety and improves cognitive
10 function in the hyperammonemia rat. Sci. China Life Sci. 57, 327–335 (2014).
11 46. Silk, D. B. A., Davis, A., Vulevic, J., Tzortzis, G. & Gibson, G. R. Clinical trial: the
12 effects of a trans-galactooligosaccharide prebiotic on faecal microbiota and symptoms
13 in irritable bowel syndrome. Aliment. Pharmacol. Ther. 29, 508–518 (2009).
14 47. Azpiroz, F. et al. Effects of scFOS on the composition of fecal microbiota and anxiety
15 in patients with irritable bowel syndrome: a randomized, double blind, placebo
16 controlled study. Neurogastroenterol. Motil. 29, e12911 (2017).
17 48. Roman, P. et al. A Pilot Randomized Controlled Trial to Explore Cognitive and
18 Emotional Effects of Probiotics in Fibromyalgia. Sci. Rep. 8, 10965 (2018).
19 49. Reale, M. et al. Daily intake of Lactobacillus casei Shirota increases natural killer cell
20 activity in smokers. Br. J. Nutr. 108, 308–314 (2012).
21 50. Sanchez, M. et al. Effects of a Diet-Based Weight-Reducing Program with Probiotic
22 Supplementation on Satiety Efficiency, Eating Behaviour Traits, and Psychosocial
23 Behaviours in Obese Individuals. Nutrients 9, 284 (2017).
24 51. Liu, X., Cao, S. & Zhang, X. Modulation of Gut Microbiota–Brain Axis by Probiotics,
32 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Prebiotics, and Diet. J. Agric. Food Chem. 63, 7885–7895 (2015).
2 52. Vaghef-Mehrabany, E. et al. Probiotic supplementation improves inflammatory status
3 in patients with rheumatoid arthritis. Nutrition 30, 430–435 (2014).
4 53. Haller, S. P. W., Cohen Kadosh, K., Scerif, G. & Lau, J. Y. F. Social anxiety disorder
5 in adolescence: How developmental cognitive neuroscience findings may shape
6 understanding and interventions for psychopathology. Developmental Cognitive
7 Neuroscience 13, 11–20 (2015).
8 54. Bravo, J. A. et al. Ingestion of Lactobacillus strain regulates emotional behavior and
9 central GABA receptor expression in a mouse via the vagus nerve. Proc. Natl. Acad.
10 Sci. U. S. A. 108, 16050–5 (2011).
11 55. Collins, S. & Reid, G. Distant Site Effects of Ingested Prebiotics. Nutrients 8, (2016).
12 56. Luján, R., Shigemoto, R. & López-Bendito, G. Glutamate and GABA receptor
13 signalling in the developing brain. Neuroscience 130, 567–580 (2005).
14 57. Morgenroth, E. et al. Altered relationship between prefrontal glutamate and activation
15 during cognitive control in people with high trait anxiety. Cortex 117, 53–63 (2019).
16 58. Hakamata, Y. et al. Attention bias modification treatment: a meta-analysis toward the
17 establishment of novel treatment for anxiety. Biol. Psychiatry 68, 982–90 (2010).
18 59. Ghassemzadeh, H., Rothbart, M. K. & Posner, M. I. Anxiety and Brain Networks of
19 Attentional Control. Cogn. Behav. Neurol. 32, 54–62 (2019).
20
33 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Supplementary material
2 Supp. Table 1. Means and non-parametric test significance values of food diary entries for
3 the first and final four days of supplement intake.
Macro as % of total energy Baseline Follow Up Within (time) p Mean (SD) Mean (SD) Energy intake (Total, Kcal) 1631.67 1654.63 GOS (338.08) (393.85) >0.999 1921.61 1905.29 Placebo (418.32) (461.38) 0.353 Between (group) p 0.009 0.025 Carbohydrates GOS 45.28 (7.12) 45.66 (7.09) 0.402 Placebo 47.19 (6.41) 47.83 (7.15) 0.498 Between (group) p 0.536 0.416 Fat GOS 36.05 (6.54) 35.37 (5.73) 0.675 Placebo 35.01 (6.04) 34.68 (6.21) 0.800 Between (group) p 0.490 0.475 Protein GOS 16.18 (4.54) 16.08 (4.46) 0.529 Placebo 15.35 (4.33) 14.90 (4.17) 0.076 Between (group) p 0.703 0.575 Dietary Saturated Fat GOS 13.53 (6.03) 13.10 (5.98) 0.834 Placebo 11.64 (3.12) 11.64 (3.08) 0.673 Between (group) p 0.381 0.489 Sugars GOS 18.85 (7.61) 16.24 (4.92) 0.010 Placebo 18.95 (6.79) 19.27 (8.21) 0.715 Between (group) p 0.942 0.287 Alcohol GOS 2.35 (4.15) 2.73 (4.32) 0.418 Placebo 2.44 (3.90) 2.60 (3.97) >0.999 Between (group) p 0.965 0.972 4 5
34 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Supp. Table 2. ANCOVA interaction for SRMs
term df F p.value etasq power Anxiety Measures Trait Baseline 1 129.89 0 0.688 1.00 Group 1 0.14 0.707 0.001 0.07 Anxiety 1 11.15 0.002 0.059 0.92 Intervention:Anxiety 1 5.58 0.023 0.03 0.66 Residuals 42 State Baseline 1 32.84 0 0.396 1.00 Group 1 0.31 0.581 0.004 0.09 Anxiety 1 4.88 0.033 0.059 0.60 Intervention:Anxiety 1 1.85 0.181 0.022 0.27 Residuals 43 SAS Baseline 1 171.70 0 0.795 1.00 Group 1 0.03 0.859 0 0.05 Anxiety 1 0.34 0.561 0.002 0.09 Intervention:Anxiety 1 0.80 0.377 0.004 0.15 Residuals 43 Mood Measures BDI Baseline 1 65.62 0 0.575 1.00 Group 1 1.80 0.186 0.016 0.27 Anxiety 1 2.79 0.102 0.024 0.39 Intervention:Anxiety 1 0.88 0.354 0.008 0.16 Residuals 43 MFQ Baseline 1 26.83 0 0.354 1.00 Group 1 0.25 0.622 0.003 0.08 Anxiety 1 5.22 0.027 0.069 0.63 Intervention:Anxiety 1 0.52 0.475 0.007 0.11 Residuals 43 Thought Regulation Reappraisal Baseline 1 23.74 0 0.335 1.00 Group 1 0.26 0.616 0.004 0.08 Anxiety 1 2.55 0.118 0.036 0.36 Intervention:Anxiety 1 1.28 0.264 0.018 0.21 Residuals 43 Suppression Baseline 1 36.19 0 0.445 1.00 Group 1 1.64 0.208 0.02 0.25 Anxiety 1 0.32 0.574 0.004 0.09 Intervention:Anxiety 1 0.15 0.703 0.002 0.07 Residuals 43 TCAQ Baseline 1 104.91 0 0.66 1.00 Group 1 0.64 0.427 0.004 0.13 Anxiety 1 9.81 0.003 0.062 0.88 Intervention:Anxiety 1 0.62 0.434 0.004 0.12 Residuals 43 Sleep PSQI Baseline 1 26.72 0 0.372 1.00 35 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
Group 1 0.14 0.713 0.002 0.07 Anxiety 1 1.88 0.177 0.026 0.28 Intervention:Anxiety 1 0.10 0.749 0.001 0.06 Residuals 43 1
2
36 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 Supp. Table 3. Descriptive statistics for bacterial diversity by intervention and anxiety group.
Baseline Follow up Mean (SD) Mean (SD) Anxiety Intervention High GOS 4.62 (1.03) 4.65 (0.93) Placebo 4.76 (0.61) 5.08 (0.85) Low GOS 4.99 (0.68) 4.95 (0.66) Placebo 4.93 (0.58) 5.28 (0.59) 2
3
37 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1
2 Supp. Figure 1. Differences found in genera in GOS group from baseline to follow-up, with
3 placebo group included for comparison. Boxplots enclose data within the 25th-75th
4 percentiles with whiskers a maximum of 1.5 times the distance of box range. Median is
5 indicated by horizontal line, and outlying data points plotted.
38 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1
2 Supp. Figure 2. Proteobacteria genera which significantly increased in the placebo group
3 from baseline to follow-up. GOS group data is shown for comparison. While these bacteria
4 are also present in the GOS group, the increase at follow-up is not as substantial as that in
5 the placebo group. Boxplots enclose data within the 25th-75th percentiles with whiskers a
6 maximum of 1.5 times the distance of box range. Median is indicated by horizontal line, and
7 outlying data points plotted.
8
39 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1
2 Supp. Figure 3. Baseline differences in genera between groups, with follow-up data
3 included for comparison. Boxplots enclose data within the 25th-75th percentiles with whiskers
4 a maximum of 1.5 times the distance of box range. Median is indicated by horizontal line,
5 and outlying data points plotted.
40 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1
2 Supp. Figure 4. Intervention group differences at follow-up. Column A. Bacteroidetes
3 genera Prevotella and Sphingobacterium are decreased for the GOS group compared to the
4 placebo group. Column B. Firmicutes genera again all reduced in the GOS group compared
41 medRxiv preprint doi: https://doi.org/10.1101/19011403; this version posted December 4, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license .
1 to the placebo group, and column C. Actinobacteria genera Actinomyces and Atopobium
2 similarly are reduced in the GOS compared to the placebo intervention group. Boxplots
3 enclose data within the 25th-75th percentiles with whiskers a maximum of 1.5 times the
4 distance of box range. Median is indicated by horizontal line, and outlying data points
5 plotted.
42