Significant outcomes
We anticipate that this systematic review will identify and describe the following:
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The role of the intestinal microbiome in paediatric neurological disorders.
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The relationship between early life alterations of the gut microbiome and the development of later life neurological disorders.
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Specific bacterial taxa of the intestinal microbiome that have been implicated in the pathogenesis or treatment of paediatric neurological disorders.
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Microbiota-derived metabolites and their effect on neurotransmitter balance and neuroglia modulation in neurodevelopmental, neuropsychiatric, and neurodegenerative disorders.
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The role of the gut microbiome in autoimmunity, immunomodulation, and neuroinflammation associated with paediatric neurodevelopmental, neuropsychiatric, and neurodegenerative disorders.
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An exploration of host–microbiome interactions between intestinal microbiota and the intestinal mucosa and their potential effect on paediatric neurodevelopmental, neuropsychiatric, and neurodegenerative disorders.
This will also be the first review to explore microbiota-based interventions that have been assessed for their role in improving symptoms of paediatric neurological disorders, including FMT, probiotics, and prebiotic-based therapies and dietary interventions.
Limitations
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This is the first study to evaluate the strength of available evidence on the association between paediatric neuropathologies and the intestinal microbiome, as well as evidence for the efficacy of microbiota-based therapeutics in managing these conditions.
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A systematic review of the prospective, retrospective, cohort, and case–control studies will be performed as per PRISMA-P guidelines using the CASP checklist.
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Available paediatric-based literature on this topic may be limited, particularly as we will be eliminating case series, case studies, and expert opinions to maintain data integrity and high-quality level of evidence.
Introduction
The gut–brain axis refers to the bidirectional communication that occurs between the gastrointestinal tract and the central nervous system (CNS) (Mayer et al., Reference Mayer, Tillisch and Gupta2015). This network of highly integrated communication is facilitated by neural, hormonal, immune, endocrine, and metabolic pathways and is essential for the maintenance of homeostasis (Westfall et al., Reference Westfall, Lomis, Kahouli, Dia, Singh and Prakash2017). The importance of the gut–brain axis in health and disease is highlighted by associations between chronic intestinal inflammation, dysregulation of the immune system, and alterations in gut microbiota and its respective metabolites. Changes in immune activation, neuronal apoptosis, and neurotransmitter concentrations have all been associated with changes in the CNS (Forsythe et al., Reference Forsythe, Bienenstock and Kunze2014; Stilling et al., Reference Stilling, Dinan and Cryan2014; Evrensel & Ceylan, Reference Evrensel and Ceylan2015; Dinan & Cryan, Reference Dinan and Cryan2017). The clinical manifestations of disruptions in this axis have been extensively studied in mood disorders (Foster & McVey Neufeld, Reference Foster and McVey Neufeld2013; Liu & Zhu, Reference Liu and Zhu2018), and are becoming increasingly recognised as aggravators in the development of adult-onset neurodegenerative diseases such as Alzheimer’s (Hu et al., Reference Hu, Wang and Jin2016; Kowalski & Mulak, Reference Kowalski and Mulak2019) and Parkinson’s disease (Houser & Tansey, Reference Houser and Tansey2017; Caputi & Giron, Reference Caputi and Giron2018). Limited research has investigated the role of the intestinal microbiome in paediatric neuropathologies.
Initial development of the infant microbiome through in utero exposure is controversial as the placenta contains no microbiota, but may contain potential pathogens (Charbonneau et al., Reference Charbonneau, Blanton, DiGiulio, Relman, Lebrilla, Mills and Gordon2016; Stinson et al., Reference Stinson, Boyce, Payne and Keelan2019). Instead, the majority of bacterial colonisation begins with parturition (Jašarević et al., Reference Jašarević, Morrison and Bale2016; Warner, Reference Warner2019) as the neonate is exposed to microbes during vaginal delivery and close contact with maternal feces (Jost et al., Reference Jost, Lacroix, Braegger, Rochat and Chassard2014; Obata & Pachnis, Reference Obata and Pachnis2016). Mode of feeding also plays an important role in early life bacterial colonisation (Belkaid & Hand, Reference Belkaid and Hand2014; Jost et al., Reference Jost, Lacroix, Braegger, Rochat and Chassard2014). The infant microbiome undergoes further expansion and diversification through early childhood, stabilising by approximately 2 years of age (Braniste et al., Reference Braniste, Al-Asmakh, Kowal, Anuar, Abbaspour, Toth, Korecka, Bakocevic, Ng, Kundu, Gulyas, Halldin, Hultenby, Nilsson, Hebert, Volpe, Diamond and Pettersson2014; Jašarević et al., Reference Jašarević, Morrison and Bale2016). Subsequent alterations to the gut microbiota profile have been observed through adolescence with final stabilisation in adulthood (Heijtz et al., Reference Heijtz, Wang, Anuar, Qian, Bjorkholm, Samuelsson, Hibberd, Forssberg and Pettersson2011). Upon the colonisation of the GI tract at birth, gut microbes establish a symbiotic relationship with the intestinal epithelium, where they play a crucial role in training the innate and adaptive immune systems to select and calibrate responses against pathogens while maintaining tolerance towards host- and commensal-derived molecular profiles (Belkaid & Hand, Reference Belkaid and Hand2014). This intimate crosstalk between the microbiota and the immune system preserves the intestinal mucosal integrity and barrier function. Perturbations of gut microbiota composition in early life have been shown to affect intestinal barrier permeability, with consequent inappropriate translocation of bacterial-derived products and antigens that can reach and cross the blood–brain barrier, which is still immature at this stage, leading to microglia hyperactivation in the CNS and neuroinflammation (Fiorentino et al., Reference Fiorentino, Sapone, Senger, Camhi, Kadzielski, Buie, Kelly, Cascella and Fasano2016). On the other hand, disturbances of the microbiota–immune system axis in early life could favour potential infections from pathogens that share molecular mimicry with host antigens, causing immunological cross-reactions and autoimmunity, all conditions associated with the pathogenesis of some neurodevelopmental (Hughes et al., Reference Hughes, Mills, Rose and Ashwood2018) and neuroinflammatory disorders (Haase et al., Reference Haase, Haghikia, Wilck, Müller and Linker2018).
Disruptions in intestinal bacterial colonisation during the critical windows of development in early life have been attributed to various exogenous insults: intrapartum maternal antibiotic use, mode of infant delivery, perinatal feeding practice, and early life exposures to antibiotics (Carabotti et al., Reference Carabotti, Scirocco, Maselli and Severi2015; Dinan & Cryan, Reference Dinan and Cryan2017). Animal models have helped elucidate the role of gut microbiota in modulating enteric neural maturation and establishment of neural circuits (Heijtz et al., Reference Heijtz, Wang, Anuar, Qian, Bjorkholm, Samuelsson, Hibberd, Forssberg and Pettersson2011; Vasquez, Reference Vasquez2017), priming the immune system to discriminate self from non-self-antigens (Houser & Tansey, Reference Houser and Tansey2017; Vuong & Hsiao, Reference Vuong and Hsiao2017), and metabolising short-chain fatty acids essential for gut (Dinan & Cryan, Reference Dinan and Cryan2017) and brain health (Carabotti et al., Reference Carabotti, Scirocco, Maselli and Severi2015). Germ-free (GF) mice have been used to show alterations in multiple neurotransmitters and signalling pathways including the hippocampus and amygdala, in contrast to conventionalised animals (Bercik et al., Reference Bercik, Denou, Collins, Jackson, Lu, Jury, Deng, Blennerhassett, Macri, McCoy, Verdu and Collins2011; Braniste et al., Reference Braniste, Al-Asmakh, Kowal, Anuar, Abbaspour, Toth, Korecka, Bakocevic, Ng, Kundu, Gulyas, Halldin, Hultenby, Nilsson, Hebert, Volpe, Diamond and Pettersson2014). While animal models have shown clear impacts of intestinal microbiota on brain development and neuropathologies, translation of this work to human hosts has been complicated by genetic, epigenetic, and environmental factors (Putignani et al., Reference Putignani, Del Chierico, Petrucca, Vernocchi and Dallapiccola2014). While directly assessing the effects of specific microbial species on brain development is generally not feasible for human study, early life alterations in the gut microbiome have been associated with various paediatric neuropathologies including: neurodevelopmental disorders such as autism spectrum disorder (ASD) (Vasquez, Reference Vasquez2017; Vuong & Hsiao, Reference Vuong and Hsiao2017), attention deficit hyperactivity disorder (ADHD) (Cenit et al., Reference Cenit, Nuevo, Codoñer-Franch, Dinan and Sanz2017), and Rett syndrome (Borghi et al., Reference Borghi, Borgo, Severgnini, Savini, Casiraghi and Vignoli2017); and neuropsychiatric disorders, such as schizophrenia, mood disorders, and dementia (Stuchlik & Sumiyoshi, Reference Stuchlik and Sumiyoshi2014) Due to the impact of intestinal dysbiosis on the onset and expression of these pathologies, there is increasing interest in investigating the role of microbiota-based treatment approaches. Probiotics, prebiotics, and fecal microbiota transplantation (FMT) (Dinan & Cryan, Reference Dinan and Cryan2017; Westfall et al., Reference Westfall, Lomis, Kahouli, Dia, Singh and Prakash2017) have received considerable attention for their potential roles in manipulating the intestinal microbiome to a ‘healthier’ milieu, in an effort to offer symptomatic improvement for these neurological disorders.
To date, knowledge about the role of the gut microbiome in paediatric brain development remains limited. This will be the first rigorous systematic review attempting to document the role of the gut microbiome in paediatric neurological disorders. There is a clear need to investigate the relationship between early life alterations to the gut microbiome and the development of later life neurological disorders, particularly as early onset disease may be most amenable to intervention. The review will attempt to identify specific bacterial taxa of the intestinal microbiome that have been implicated in the pathogenesis or treatment of paediatric neurodevelopmental, neuropsychiatric, and neurodegenerative disorders. We will discuss hormonal regulation as well as inflammatory and other biochemical pathways associated with these relevant disorders. Further, we will explore microbiota-based interventions that have been examined for their role in improving symptoms associated with paediatric neuropathologies, including FMT, probiotics, and prebiotic-based therapies.
Objectives
To conduct a systematic review on the role of the gut microbiome in paediatric neurological disorders.
Methods and analysis
Study design
As is outlined by Grant and Booth (Grant & Booth, Reference Grant and Booth2009), we will be conducting a systematic review of the relevant literature. In this context, we will be systematically searching, appraising, and synthesising evidence surrounding the gut microbiome in paediatric neurological disorders, including neurodevelopmental, neuropsychiatric, and neurodegenerative diseases. We aim to draw upon a wider range of study designs that incorporate quantitative, qualitative, and mixed-method studies.
This review will follow the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) protocols checklist (Liberati et al., Reference Liberati, Altman, Tetzlaff, Mulrow, Gøtzsche, Ioannidis, Clarke, Devereaux, Kleijnen and Moher2009). The systematic review protocol was prospectively registered on PROSPERO (ID: CRD42020158734) (National Institute for Health Research, 2020).
Data management
The search results will be imported into the Mendeley reference management software (https://www.mendeley.com). Once the two rounds of study identification have been completed, we will be using Covidence (https://www.covidence.org), a review management software program that is in partnership with Cochrane collaboration. Covidence is a core component of Cochrane’s review production toolkit and will be used to assess the risk of bias within the identified studies as well as assist with data extraction.
Data sources and search strategy
Relevant studies will be identified using PubMed, Cochrane Library, and OVID electronic databases. Articles published between January 1980 and February 2021 will be considered. The following search terms will be used to identify potential articles: (FMT OR fecal microbiota OR microbiome) AND (neurodevelopmental) AND (paediatric OR children), (FMT OR fecal microbiota OR microbiome) AND (neurodegenerative) AND (paediatric OR children), (FMT OR fecal microbiota OR microbiome) AND (neuropsychiatric disorder) AND (paediatric OR children). Further, we will explore the relationship between the gut microbiome and subsequent immunomodulation, nutritional modulation, molecular mimicry, and microglial responses involved in paediatric neurological disorders. Our review will also investigate key concepts including epitopes, lymphocytic responses, molecular mimicry, antigenic cross-reactions, autoimmunity, and glial activation. To achieve this, the following search terms will be used to identify potential articles: (microbiome OR microbiota OR gut microbiome) AND (immunomodulation OR autoimmunity OR inflammation) AND (neurodevelopmental) AND (paediatric OR children), (microbiome OR microbiota OR gut microbiome) AND (immunomodulation OR autoimmunity OR inflammation) AND (neurodegenerative) AND (paediatric OR children), (microbiome OR microbiota OR gut microbiome) AND (immunomodulation OR autoimmunity OR inflammation) AND (neuropsychiatric disorder) AND (paediatric OR children).
We will implement a rigorous search strategy that involves two rounds of literature review, using a three-step method in each round. The first round will involve a review of articles from the search results of the databases; the second round will involve a review of works cited by those articles identified in the first round (Table 1). Titles, abstracts, and full texts will be independently screened by at least two authors (L.H., J.P., M.F., V.C., E.H., M.M., N.P.). Articles will be excluded if they are unrelated or meet the exclusion criteria outlined in Table 1.
Inclusion and exclusion criteria
Study selection
Titles and abstracts of the studies will be screened for eligibility by two independent reviewers (MF and LH) using criteria outlined in Table 1. Conflicts will be resolved by discussion between the two reviewers, and if needed, by adjudication of a third independent reviewer (J.P., E.H., M.M., N.P.). The full text of all studies selected during screening will be reviewed independently by two reviewers (M.F. and L.H.) with disagreement resolved as earlier described. A PRISMA flow chart will be used to show the details of the selection process (Fig. 1).
Systematic review protocol flow diagram.
Data extraction
Data extraction will be completed by two reviewers (M.F. and L.H.) using a pre-piloted Microsoft Excel data extraction form. Data extraction will be checked for accuracy and completeness of the data by other members of the research team (N.P., J.P., E.H., M.M., and V.C.). Collected data will include the year of publication, country, setting, population, specific type of neuropathology, and microbiome-related data. The draft data extraction tool will be modified and revised during the process of extracting data from each included study. Any modifications will be detailed in the final systematic review report. Any disagreements that arise between the reviewers will be resolved through discussion. If consensus cannot be reached, the senior scientist (N.P.) will be consulted to offer a final decision.
Inclusion and exclusion criteria
The inclusion and exclusion criteria are summarised in Table 1.
Definition of neuropsychiatric disorders
Neuropsychiatric disorders are characterised by their influence on an individual’s brain activity, and subsequently their emotional state of mind (Taber et al., Reference Taber, Hurley and Yudofsky2010). Although their symptoms vary by pathophysiology, all neuropsychiatric disorders interrupt day-to-day lifestyle, impacting the individual, their social network, and society as a whole (Hyman, Reference Hyman2008). According to the World Health Organization, neuropsychiatric disorders account for 20% of health-related disabilities (Kessler et al., Reference Kessler, Chiu, Demler and Walters2005). These disorders are characterised by high prevalence, early onset, and contribute as primary risk factors for suicide (Kessler et al., Reference Kessler, Chiu, Demler and Walters2005; Hyman, Reference Hyman2008; Insel, Reference Insel2009).
Quality assessment
We will assess the quality of the included studies using the appropriate Critical Appraisal Skills Programme (CASP) checklist (https://casp-UKnet/) based on study methodology. Although CASP does not provide a numeric score, it will enable a systematic assessment of the trustworthiness, relevance, and results of published papers.
Level of evidence assessment
Level of evidence will be assessed using established methods (Obremskey et al., Reference Obremskey, Pappas, Attallah-Wasif, Tornetta and Bhandari2005). Accordingly, the articles will be assessed in compliance with a hierarchy of evidence. Randomised controlled trials and high-quality studies will be included. The highest quality studies are prospective cohort studies and are considered to be level I; lower quality (smaller sample sizes and weaker methodology prospective studies and retrospective studies) are considered to be level II; cross-sectional and case–control studies are considered to be level III; case series studies are level IV; and finally, expert opinions are considered to be level V.
Patient and public involvement
There will be no patients or members of the public involved in this systematic review.
Data analysis and synthesis
The extracted data and results will be presented as a table to help summarise and map the existing literature. Descriptive data will be tabulated (publication, country, setting, population, specific type of pathology, and microbiome-related data) within evidence tables. If sufficient evidence exists, we will explore the possibility of conducting further meta-analyses. Data relating to specific neuropsychiatric disorders and gut microbiome factors will be grouped to derive common themes, and their relationships will be explored. These themes will be organised to provide tabular and narrative summaries of key characteristics.
The strength of evidence will be assessed using the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) approach (Andrews et al., Reference Andrews, Guyatt, Oxman, Alderson, Dahm, Falck-Ytter, Nasser, Meerpohl, Post, Kunz, Brozek, Vist, Rind, Akl and Schünemann2013). The GRADE approach uses four quality levels such as high, moderate, low, and very low. The strength of evidence will be downgraded by one level according to the following criteria: (1) limitations in the design and implementation of available studies suggesting risk of bias; (2) indirectness of evidence; (3) unexplained heterogeneity or inconsistency; (4) imprecision of results; and (5) high probability of publication bias. Three criteria for upgrading the certainty of evidence include large magnitude of effect, dose–response, and residual confounding opposing the observed effect. The certainty of evidence will be reported as high, moderate, low, or very low. High certainty means that further research is very unlikely to change our confidence in the estimate of effect; moderate certainty means that further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate; low certainty means that further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate; and very low certainty means that we are very uncertain about the estimate. Assessment will be reported in the GRADE summary of findings tables.
Ethics and dissemination
Our study is a systematic review of previously published literature and as such, ethical approval is not necessary according to the Hamilton Integrated Research Ethics Board. In addition to the prospective publication of our current protocol, we will be disseminating our results through local and international conferences to encourage broader uptake. The final manuscript will be submitted for peer-reviewed publication.
Author contributions
All authors (LH, JP, MF, VC, EH, MM, and NP) contributed to the study conceptualisation and study design. Authors LH, JP, and MF contributed to the writing of the first draft of the manuscript. Authors VC, EH, MM, and NP contributed to the review and revision of the manuscript. All authors read and approved the final version of the manuscript.
Financial support
None.
Conflict of interest
The authors have no conflicts of interest to declare.
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