Dysregulation of synaptic pruning as a possible link between intestinal microbiota dysbiosis
and neuropsychiatric disorders
Eltokhi, Ahmed; Janmaat, Isabel E.; Genedi, Mohamed; Haarman, Bartholomeus C. M.;
Sommer, Iris E. C.
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Journal of Neuroscience Research
DOI:
10.1002/jnr.24616
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Eltokhi, A., Janmaat, I. E., Genedi, M., Haarman, B. C. M., & Sommer, I. E. C. (2020). Dysregulation of
synaptic pruning as a possible link between intestinal microbiota dysbiosis and neuropsychiatric disorders.
Journal of Neuroscience Research, 98(7), 1335-1369. https://doi.org/10.1002/jnr.24616
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J Neuro Res. 2020;98:1335–1369. wileyonlinelibrary.com/journal/jnr
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1335Received: 3 September 2019
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Revised: 16 February 2020|
Accepted: 26 February 2020DOI: 10.1002/jnr.24616
R E V I E W
Dysregulation of synaptic pruning as a possible
link between intestinal microbiota dysbiosis and
neuropsychiatric disorders
Ahmed Eltokhi
1| Isabel E. Janmaat
2| Mohamed Genedi
2|
Bartholomeus C. M. Haarman
3| Iris E. C. Sommer
2This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
© 2020 The Authors. Journal of Neuroscience Research published by Wiley Periodicals, Inc. Edited by Karina Alvina. Reviewed by Pilar Codoner-Franch and Cecilia Ximenez.
The peer review history for this article is available at https://publo ns.com/publo n/10.1002/jnr.24616.
1Department of Neurology and Epileptology,
Hertie Institute for Clinical Brain Research, Eberhard Karls University Tubingen, Tubingen, Germany
2Department of Biomedical Sciences, Cells
& Systems, University Medical Centre Groningen, University of Groningen, Groningen, the Netherlands
3Department of Psychiatry, University
Medical Centre Groningen, University of Groningen, Groningen, the Netherlands Correspondence
Ahmed Eltokhi, Department of Neurology and Epileptology, Hertie Institute for Clinical Brain Research, Eberhard Karls University Tubingen, Otfried-Müller-Straße 27, Tubingen 72076, Germany.
Email: ahmed.eltokhi@uni-tuebingen.de Funding information
The Stanley Medical Research Institute and ZonMW
Abstract
The prenatal and early postnatal stages represent a critical time window for human
brain development. Interestingly, this window partly overlaps with the maturation of
the intestinal flora (microbiota) that play a critical role in the bidirectional
communi-cation between the central and the enteric nervous systems (microbiota-gut-brain
axis). The microbial composition has important influences on general health and the
development of several organ systems, such as the gastrointestinal tract, the immune
system, and also the brain. Clinical studies have shown that microbiota alterations are
associated with a wide range of neuropsychiatric disorders including autism
spec-trum disorder, attention deficit hyperactivity disorder, schizophrenia, and bipolar
dis-order. In this review, we dissect the link between these neuropsychiatric disorders
and the intestinal microbiota by focusing on their effect on synaptic pruning, a vital
process in the maturation and establishing efficient functioning of the brain. We
dis-cuss in detail how synaptic pruning is dysregulated differently in the aforementioned
neuropsychiatric disorders and how it can be influenced by dysbiosis and/or changes
in the intestinal microbiota composition. We also review that the improvement in the
intestinal microbiota composition by a change in diet, probiotics, prebiotics, or fecal
microbiota transplantation may play a role in improving neuropsychiatric functioning,
which can be at least partly explained via the optimization of synaptic pruning and
neuronal connections. Altogether, the demonstration of the microbiota's influence
on brain function via microglial-induced synaptic pruning addresses the possibility
that the manipulation of microbiota-immune crosstalk represents a promising
strat-egy for treating neuropsychiatric disorders.
K E Y W O R D S
glial cells, neural development, neurodegenerative diseases, neurodevelopmental disorders, oligodendrocytes
1 | INTRODUCTION
At the most fundamental level, brain function is based mainly on computations performed by synapses. Perturbations in physiological synaptic structure and function and dysregulated synaptic forma-tion, elimination and plasticity have been hypothesized to underlie altered neuronal function in complex neuropsychiatric disorders, such as autism spectrum disorder (ASD) and schizophrenia (SZ) (Wang, Christian, Song, & Ming, 2018). At the early stages of life, synapse formation (synaptogenesis) exceeds elimination, yielding excessive synapses essential for the assembly of neural networks (Bruer, 1999). Subsequently, synaptic elimination/pruning outpaces synaptogenesis, providing selection and maturation of synapses and neural circuits from childhood through adolescence (Tang et al., 2014). Different patterns of dysregulated synaptic pruning have been linked to various neuropsychiatric phenotypes, confirming the importance of the balanced synaptic formation and pruning in normal brain function. Recent studies have pointed to a key role for microglia, the innate immune cells of the central nervous system (CNS), in synaptic pruning by purging the brain of infrequently used synapses (Weinhard et al., 2018).
In mammals, microglial activation and function during devel-opmentally sensitive periods can be modulated by the microbiota (Erny et al., 2015), the different resident phyla and bacterial species in the gastrointestinal (GI) system (Dickerson, Severance, & Yolken, 2017; Fond et al., 2015; Nemani, Hosseini Ghomi, McCormick, & Fan, 2015). Many causes can alter the well-being of the micro-biota including administration of antibiotics or non-steroidal anti- inflammatory medicines, herbicides, ingredients present in food (sugar or gluten) or in water (chlorine) (Larroya-Garcia, Navas-Carrillo, & Orenes-Pinero, 2019). In turn, the imbalance in microbiota composition (dysbiosis) can affect the function of neuronal circuits via synaptic pruning alteration (Tognini, 2017). Indeed, the current data indicate that various neuropsychiatric disorders are associated with microbiota alterations (Cenit, Sanz, & Codoñer-Franch, 2017; Kim & Shin, 2018). Hence, a better understanding of the effect of intestinal microbiota dysbiosis on synaptic pruning can pave the way to enhance the treatment outcomes of neuropsychiatric disorders.
2 | SYNAPTOGENESIS AND SYNAPTIC
PRUNING DURING BR AIN DEVELOPMENT
Synaptogenesis is a complex multifactorial developmental process which enables the formation of synapses between neurons. Synapse formation is essential for all nervous system functions including es-tablishing neural circuits and ultimately expressing complex behav-ior (Hong & Park, 2016). Across mammalian species, neurons present at birth undergo a period of overproduction of their arborization and synaptic contacts to increase synaptic density (Semple, Blomgren, Gimlin, Ferriero, & Noble-Haeusslein, 2013). In humans, the thick-ness of the cortex typically increases in the first few years of life as a result of excessive synapse formation (Tau & Peterson, 2010), withdifferent cortical regions showing their peaks of synapse formation periods (Huttenlocher & Dabholkar, 1997). For example, synaptic density in the primary visual cortex reaches its peak between the ages of 4 and 12 months (Tau & Peterson, 2010). Synaptogenesis in the prefrontal cortex that requires remodeling to achieve fully ma-ture and complex behavior begins about the same time as in the vis-ual cortex, but it continues to reach its peak through the second and third year of life (Huttenlocher, de Courten, Garey, & Van der Loos, 1982; Huttenlocher & Dabholkar, 1997; Kostović, Judaš, Petanjek, & Šimić, 1995; Lenroot & Giedd, 2006).
Later in life, at the time of early adolescence, cortical thickness decreases by pruning weak and redundant synaptic connections, and strengthening the remaining synapses (Sowell, Thompson, & Toga, 2004; Wang et al., 2018). Synaptic pruning is a crucial process to enhance neuronal transmission and to establish the finely tuned circuitry by eliminating ineffective synapses and strengthening the vital neuronal connections, which allows for more efficient process-ing of adult cognition. In mammals, axonal and dendritic processes constitute approximately 60% of cortical volume (Tau & Peterson, 2010), and pruning of these processes may represent the source of cortical thinning (Paus, Keshavan, & Giedd, 2008).
Synaptic pruning begins in late gestation and becomes increas-ingly active postnatally (Tau & Peterson, 2010). The time course for pruning differs across brain regions, with sensory and motor corti-ces undergoing dramatic fine-tuning after birth, followed by asso-ciation cortices and the corpus callosum, and later by regions that subserve higher cognitive functions (Levitt, 2003). In early childhood (2 and 7 years of age), neuronal density in layer III of the prefron-tal cortex decreases from 55% to approximately 10% above adult levels (Huttenlocher, 1979). During later childhood (7–15 years of age), synaptic density in the frontal cortex decreases by approxi-mately 40% (Lidow, Goldman-Rakic, Gallager, & Rakic, 1991). These synaptic changes occur in the absence of any significant neuronal loss and are accompanied by a reduction in the expression of genes involved in axonal and synaptic functions (Colantuoni et al., 2011). The continuous cortical thinning via synaptic pruning throughout
Significance
The association between the intestinal microbiota and brain function is not fully understood. In this review, we propose synaptic pruning dysregulation as a possible link between microbiota dysbiosis and neuropsychiatric disorders in-cluding autism, schizophrenia, bipolar and attention deficit hyperactivity disorders. To this end, the alleviation of neu-ropsychiatric symptoms via improving the intestinal microbi-ota composition might be partly explained by the modulation of microglial function, leading to a modification in neuronal connections. Therefore, the microglial activity and its effect on synaptic pruning may be good markers for testing the ef-ficacy of probiotics and prebiotics as supportive therapeutic approaches for neuropsychiatric disorders.
late childhood and adolescence reflects ongoing maturation of neu-ral networks which underlies behavioneu-ral changes at these periods (Semple et al., 2013).
3 | DYSREGUL ATED SYNAPTIC PRUNING
IN NEUROPSYCHIATRIC DISORDERS
Disturbed synaptic pruning has been linked to deficits in neuronal circuitry with behavioral impairments as a consequence. Over the last decade, mutations in several genes that encode the required proteins for synapse formation, development, plasticity, and pruning were linked to the psychopathology of multiple complex neuropsy-chiatric disorders including ASD, SZ, attention deficit hyperactivity disorder (ADHD) and bipolar disorder (BD) (Wang et al., 2018; Zoghbi & Bear, 2012). This supports the hypothesis that neuropsychiatric disorders are, in part, the consequences of a developmental synap-topathy. Interestingly, a survey of over 9,000 people representative of the US population in the period between February 2001 and April 2003 has indicated that the peak age of onset for having any mental health disorder is 14 years (Kessler et al., 2005). Moreover, among adult cases with neuropsychiatric disorders, 73.9% have developed
behavioral symptoms and received a diagnosis before 18 years of age and 50% before 15 years of age which concurrent with the peak of the synaptic pruning process (Kim-Cohen et al., 2003).
Different patterns of dysregulated synaptic pruning are asso-ciated with various neuropsychiatric phenotypes, with grey matter loss in the bilateral anterior- and subgenual cingulate cortex in schi-zoaffective disorder and BD, whereas general grey matter loss was observed for SZ (Gogtay, 2008; Mattai et al., 2011). In contrast, ac-celeration in brain growth of all regions except occipital grey matter in the early years of patients with ASD was observed (Schumann et al., 2010).
3.1 | Autism spectrum disorder
ASD is a complex neurodevelopmental disorder with a strong genetic component, which refers to a constellation of clinical conditions with two main phenotypic characteristics: impairment in social communi-cation and patterns of repetitive restrictive behavior (Berkel et al., 2018). Remarkably, the time when ASD symptoms appear or become more apparent, at around 2–3 years old, coincides with the window for the initial generalized synaptic pruning event (Figure 1).
F I G U R E 1 The onset of neuropsychiatric disorders symptoms in relation to synaptic pruning and microbiota development in the
intestine. Autism spectrum disorder and attention deficit hyperactivity disorder symptoms appear concurrent with the start of the synaptic pruning process. In contrast, schizophrenia and bipolar disorder symptoms are parallel with the end of the synaptic pruning process. The microbiota composition is continuously changed throughout the lifespan with major changes concurrent with the synaptic pruning process. The association of microbiota alteration to neuropsychiatric disorders via synaptic pruning is an important example of the signaling between the central and the enteric nervous systems (microbiota-gut-brain axis) [Color figure can be viewed at wileyonlinelibrary.com]
Some children diagnosed with ASD feature a significant excess in brain size and weight in the first year of life due to a high accel-eration rate of brain growth (Courchesne, Carper, & Akshoomoff, 2003). This involves an enlargement in different brain regions with an expansion in both grey and white matter volume as ob-served by magnetic resonance imaging (MRI) studies (Courchesne et al., 2003; Gaffney, Kuperman, Tsai, & Minchin, 1989; Hardan, Muddasani, Vemulapalli, Keshavan, & Minshew, 2006; Piven et al., 1992, 1995). Moreover, diffusion tensor images from the brains of ASD children have shown an increase in axons and myelination between neighboring areas of the brain compared with more distal connections, suggesting an increase in connectivity (Walker et al., 2012). On the microstructural scale, synaptic densities of pyra-midal neurons in the temporal lobe are observed in postmortem studies to be increased in the brains of children and adults with ASD (Hutsler & Zhang, 2010; Tang et al., 2014). Moreover, the re-duction in cortical spine density that is observed in brains of typi-cally developing adolescents is diminished in individuals with ASD (Tang et al., 2014), suggesting a deficit in pruning, at least at this later age. Besides, mice carrying rare, penetrant mutations that are found in individuals with ASD show elevated spine densities in the temporal cortex and cerebellum (Kim et al., 2017; Piochon et al., 2014; Tang et al., 2014) and deficient adolescent pruning (Tang et al., 2014). Altogether, children with ASD are believed to have excess synapses and synaptic connections in the brain due to deficits in synaptic pruning during early brain development (Tang et al., 2014), which may account for the abnormal patterns of brain connectivity in ASD (Belmonte et al., 2004).
The idea that enhanced connectivity may have disadvanta-geous effects on brain function and cognition was supported by mouse models. Mice with excessive synaptic connections due to a failure in synaptic pruning were primarily able to learn spatial lo-cations but unable to re-learn new lolo-cations (Afroz, Parato, Shen, & Smith, 2016). This indicates that too many brain connections may put limitations on the learning potential. Moreover, by im-pairing synaptic pruning in mice, they exhibited ASD-like pheno-types including social interaction deficits and repetitive behavior (Fernandez de Cossio, Guzman, van der Veldt, & Luheshi, 2017; Kim et al., 2017). A similar process to the methodology in the aforementioned mouse studies is suggested to play a role in the impairment of synaptic pruning in humans diagnosed with ASD. Therefore, there is evidence from mouse studies to support the claim that children diagnosed with ASD are believed to have in-creased synaptic connections in the brain due to deficits in syn-aptic pruning during early brain development (Tang et al., 2014). However, caution should be taken when translating mice finding to humans. Although a large variety of mouse behavioral tests are currently used and showed considerable face validity in testing the ASD core symptoms, the lack of a “human-specific” read-out resulting from complex gene–environment interactions occurring during early postnatal stages and adolescence is the main limita-tion (Pasciuto et al., 2015). Therefore, the validity of drawing solid conclusions from mice to humans is still limited.
3.2 | Attention deficit hyperactivity disorder
ADHD is a complex brain disorder marked by an ongoing pattern of inattention, hyperactivity, and impulsivity that significantly im-pacts many aspects of behavior as well as cognitive performance (Singh, Yeh, Verma, & Das, 2015). Structural MRI studies on people with ADHD have revealed a subtle but significant grey and white matter loss (Rapoport et al., 2001), which was not progressive (Castellanos et al., 2002). Moreover, cross-sectional MRI studies have shown a reduction in the size of cortico-striatal brain regions that are known to develop late in adolescence (Berger, Slobodin, Aboud, Melamed, & Cassuto, 2013; Krain & Castellanos, 2006), in the volumes of the right and left inferior-posterior cerebellar lobes (Mackie et al., 2007), and in the thickness of cerebellar brain region (Shaw et al., 2007). However, the structural development of almost all cortical regions in ADHD children was similar to non-psychiatric control subjects (Shaw et al., 2007). To this end, it is suggested that ADHD children suffer from a maturational delay due to a lag in synaptic pruning (Rubia, 2007; Shaw et al., 2007; Vaidya, 2012), which is supported by the fact that 80% of children grow out of ADHD in adulthood (Faraone et al., 2000). The cortical maturation delay in ADHD was most prominent in the lateral prefrontal cor-tex, which supports the ability to suppress inappropriate responses and thoughts, executive control of attention, evaluation of reward contingencies, and working memory (Shaw et al., 2006, 2007). In contrast, only the motor cortex had a maturation peak 4 months ahead in children diagnosed with ADHD compared to control chil-dren, which may account for the impulsivity in people with ADHD (Shaw et al., 2007).
3.3 | Schizophrenia
SZ is a complex, mental disorder characterized by an array of symp-toms including delusions, hallucinations, disorganized speech or behavior, lack of motivation, and impaired cognitive ability (Patel, Cherian, Gohil, & Atkinson, 2014). Unlike ASD, the onset of the symptoms of SZ typically occurs between the ages of 15 and 25 and coincides with later stages of synaptic pruning in the adolescent pre-frontal cortex (Selemon & Zecevic, 2015).
The association between synaptic pruning dysregulation in adoles-cence and SZ was first hypothesized by Feinberg in 1982 (Feinberg, 1982). This hypothesis was revisited in 1994 by analyzing postmortem brains which showed that excessive synaptic pruning in the excitatory glutamatergic neurons in the prefrontal cortico-cortical and -sub-cortical areas was seen in SZ neuropathology (Keshavan, Anderson, & Pettegrew, 1994). Synaptic pruning ends at the age of onset for SZ (Wang et al., 2018; Figure 1), which further links the dysregulation of synaptic pruning to the SZ pathophysiology. In one study, the grey matter volume, as a measure of the extent of synaptic pruning (Sowell, Thompson, Tessner, & Toga, 2001), was reduced in both males and fe-males diagnosed with SZ and correlated with reduced cognitive perfor-mance (Gur, Turetsky, Bilker, & Gur, 1999). This finding was replicated
in another study which showed a fourfold excess of permanent grey matter loss in SZ compared to control subjects evaluated prospectively over 5 years (Thompson et al., 2001). A meta-analysis study including over 18,000 subjects revealed that intracranial and total brain volume in patients with SZ was significantly decreased (Haijma et al., 2013). Patients with SZ revealed a specifically reduced grey matter volume in the prefrontal cortex (Zhang et al., 2016), which may account for their disturbed behavioral inhibition.
Neuropathologic studies indicated that the grey matter reduction in the brains of individuals with SZ is due to cortical thinning, with the greatest severity in the frontal lobes due to primarily shrinkage in neuropil combined with a decrease in neuronal size (Andreasen et al., 2011; Berdenis van Berlekom et al., 2019; Osimo, Beck, Reis Marques, & Howes, 2019). Moreover, the locus of complement fac-tor C4A that, among other functions, regulates synaptic pruning is one of the genetic loci significantly associated with SZ (Sekar et al., 2016). C4A has also been shown to be expressed during the postna-tal neurodevelopmenpostna-tal stage in proportion to the allelic risk associ-ation with SZ (Sekar et al., 2016). One of the functions of activated complement is the opsonization of synapses to facilitate phagocy-tosis by microglia, hence leading to enhanced pruning. In addition, neuroimaging studies confirmed the enhanced synaptic pruning in individuals with clinical high risk for developing SZ (Cannon et al., 2015). Based on the aforementioned studies, individuals with SZ are suggested to have fewer synapses due to excessive synaptic prun-ing and suboptimal fine-tunprun-ing of neural circuits mediatprun-ing motor, sensory and cognitive functions (Berdenis van Berlekom et al., 2019; Forsyth & Lewis, 2017; Mallya & Deutch, 2018; Sellgren et al., 2019).
3.4 | Bipolar disorder
BD is a chronic mental health condition that is characterized by de-pressive and (hypo)manic mood episodes, as well as an impairment in cognitive ability (Gondalia, Parkinson, Stough, & Scholey, 2019). In BD, serial MRI scanning of adolescent patients has shown significant grey matter reduction in some areas of the brain including the bilat-eral anterior and subgenual cingulate cortex (Gogtay et al., 2007). In 2012, another study has shown that individuals diagnosed with BD suffer from a disruption of the emotional control networks during development linked with synaptic pruning dysfunction, which leads to abnormal ventral prefrontal-limbic modulation causing the onset of mania (Strakowski et al., 2012). In addition, the age of onset of BD and the monoaminergic synaptic density measured with PET meas-ures were found to be interrelated (Zubieta et al., 1998).
4 | THE INFLUENCE OF MICROGLIA
ACTIVATION ON SYNAPTIC PRUNING AND
NEURONAL FUNCTION
Microglia are the innate immune cells of the CNS that account for 10%–15% of all cells found within the brain (Lawson, Perry, &
Gordon, 1992). Several studies have identified a set of critical sign-aling pathways between microglia and neurons (for a review, see [Neniskyte & Gross, 2017]). Importantly, microglia have been shown to play a major role in the synaptic pruning process by purging the brain of infrequently used synapses (Boksa, 2012; Paolicelli et al., 2011; Schafer & Stevens, 2013; Stephan, Barres, & Stevens, 2012; Trapp et al., 2007). The first indication that microglia are involved in synaptic pruning was demonstrated by a study that showed that the large-scale axonal remodeling in embryonic and early postna-tal development in cats was accompanied by a phagocytic activity of microglia and astrocytes, which were suggested to contribute to axon elimination (Berbel & Innocenti, 1988). Other studies in diverse model systems and circuits, ranging from peripheral syn-apses in the neuromuscular junctions to central synsyn-apses in the cortex, hippocampus, thalamus, and cerebellum strengthened the role of microglia in synaptic fine-tuning (Darabid, Perez-Gonzalez, & Robitaille, 2014; Hoshiko, Arnoux, Avignone, Yamamoto, & Audinat, 2012; Ichikawa et al., 2011; Paolicelli et al., 2011; Sasaki et al., 2014a, 2014b; Schafer et al., 2012; Zhan et al., 2014).
Given the evidence presented above, it may be unsurprising that the dysregulation of microglial activity, particularly over-activation, has been linked to several neuropsychiatric disorders including SZ (Bloomfield et al., 2016; De Picker, Morrens, Chance, & Boche, 2017; Doorduin et al., 2009; Marques et al., 2018; van Kesteren et al., 2017) and BD (Haarman et al., 2014). Excessive synaptic pruning mediated by microglia in SZ is further supported by genetic studies (Calabrò, Drago, Sidoti, Serretti, & Crisafulli, 2015; Cocchi, Drago, & Serretti, 2016). Genetic variants that are significantly associated with SZ include those in genes related to microglial activation path-ways that contribute to synaptic pruning in the cortex and thalamus (Neniskyte & Gross, 2017). Reducing microglial activity via anti- inflammatory agents was able to enhance the antipsychotic effect for treating negative and cognitive symptoms of SZ (De Picker et al., 2017; Kato et al., 2011; Kroken, Sommer, Steen, Dieset, & Johnsen, 2019; Levkovitz et al., 2010) and to relieve depressive and manic symptoms in BD (Edberg et al., 2018; Mousavi et al., 2017; Savitz et al., 2018). Moreover, in vitro studies of antipsychotic agents— perospirone, ziprasidone, and quetiapine—as well as lithium showed attenuation of microglial activation (Bian et al., 2008; Fabrizi et al., 2017).
Many factors including genetic predisposition, head trauma, and infection can cause microglial overactivation, hence affecting the normal brain function by influencing synaptic plasticity and synaptic elimination (Boulanger, 2009; Goshen et al., 2007; Khairova, Machado-Vieira, Du, & Manji, 2009; Lui et al., 2016; Murray & Lynch, 1998). One genetic predisposition is for the complement factor C4A gene which had a strong risk association with SZ. The phenotype of C4A shows increased synapse engulfment and thus excessive synaptic pruning (Sellgren et al., 2019; Wang, Zhang, & Gage, 2019), and the “omic” studies revealed a link between C4A and SZ pathogenesis (Birnbaum & Weinberger, 2019; van Mierlo, Schot, Boks, & de Witte, 2019). A recent meta-analysis on postmortem brain studies for the immune in-volvement in the pathogenesis of SZ showed a significant increase in
T A B LE 1 C lin ic al s tu di es o n i nt es tin al m ic ro bi ot a d ys bi os is i n p at ie nt s w ith a ut is m s pe ct ru m d is or de r, a tt en tio n d ef ic it hy pe ra ct iv ity d is or de r, s ch iz op hr en ia , o r b ip ol ar d is or de r Re fer en ce s Sa m ple s iz e M ea n a ge i n ye ar s ± SD (R an ge ) G en der (M ale / Female ) C ha ng es i n t ax on om ic c om po si tio n ( in PT c om pa re d t o N C ) A ss oc ia tio n w ith c lin ic al f ea tu re s ( in PT c om pa re d t o N C ) Li m ita tio ns /N ot es W an g, Z ho u, et a l. ( 20 19 ) • A SD : 4 3; 1 9 w ith G I i nv ol ve m en t 24 w ith ou t G I in vo lv emen t • N C : 3 1 • W ith G I p ro bl em s: 4. 2 ± 1. 5 ( 2–8 ) • W ith ou t G I pr ob le m s: 4. 5 ± 1. 8 (2– 8) • TD s 3 .5 ± 1 .6 ( 2– 6) • W ith G I pr ob le m s: ( 16 /3 ) • W ith ou t G I pr ob le m s: ( 20 /4 ) • TD S ( 18 /1 3) • Fi ve m ic ro bi om e e pi to pe s ( M Es ) w er e s ig ni fic an tly ↑ ( Fo ur w er e ve ry s im ila r t o p ep tid es f ro m hu m an g ap j un ct io n a lp ha -1 (G JA1 ), β -m yo si n h ea vy c ha in (M YH 7) , p ai re d b ox p ro te in P ax - 3 (P A X3 ), a nd e ye s a bs en t h om ol og 1 i so fo rm 4 ( EY A 1) . O ne M E f ro m Li st er io ly si n O p ro te in , d er iv ed fr om t he p at ho ge ni c m ic ro or ga ni sm Li st er ia m ono cy to gen es , w as a ls o si gn ifi ca nt ly ↑ ) • A m on g t he 2 9 M Es s ig ni fic an tly ↓ i n A SD P Ts , 1 1 M Es w er e pr ed ic te d p ep tid es f ro m p at ho ge ni c micr oo rg an is m s su ch a s T. g on di i a nd her pe s s im pl ex vi ru s • A SD P Ts h av e ↑ G I p ro bl em s • A SD P Ts w ith G I p ro bl em s s ho w ed ↑ d iv er si ty • A SD P Ts w ith /w ith ou t G I i nv ol ve m en t c ou ld b e di st in gu is he d b y t he c om po si tio n an d/ or a bu nd an ce o f M Es • N o s ig ni fic an t d iff er en ce s i n s to ol Ig A l ev el s b et w ee n A SD P Ts w ith G I p ro bl em s a nd A SD P Ts w ith ou t G I p ro bl em s • M Es h av e n ot b ee n va lid ate d • So m e c lin ic al i nd ic at or s w er e n ot c ol le ct ed i n T D chi ld re n Zh ai e t a l. (2 01 9) • A SD : 78 • N C : 5 8 • A SD : 4 .9 6 ± 1 .0 1 • N C : 4 .9 0 ± 0 .9 7 • A SD : ( 56 /2 2) • N C : ( 31 /2 7) • Si gn ifi ca nt h ig he r t ax a r ic hn es s a nd di ve rs ity o f g ut m ic ro bi ot a i n t he A SD g ro up c om pa re d t o t he N C • Th e m ic ro bi om e of th e A SD ch ild re n w as c ha ra ct er ize d b y a s ig ni fic an t in cr ea se i n n in e g en er a: Bac te ro ide s, Pa ra ba ct er oi de s, S ut te re lla , La ch no sp ira , B ac ill us , B ilop hi la , Lac to co cc us , L ac hn obac te riu m , a nd O sc ill os pir a • C ar bo n f ix at io n p at hw ay s i n pr ok ar yo te s a nd t he c itr at e c yc le w er e p os iti ve ly a ss oc ia te d w ith Bac te ro ide s, O sc ill os pir a, a nd Su tt er el la . E th er l ip id m et ab ol is m an d s po ru la tio n w er e n eg at iv el y re la te d t o Pa ra bac te ro ide s • Li m ite d p op ul at io n (C hi ne se c hi ld re n) C or et ti e t a l. (2 018 ) • A SD : 1 1 • N C : 1 4 • A SD : 3 5 ± 5. 7 • N C : 3 5 ± 8. 4 • A SD : ( 9/ 2) • N C : ( 8/ 6) • Ph yl um l ev el : ↓ Ac tin obac te ria , ↑ in Ba cte ro id ete s a nd Pr ot eobac te ria Fir m ic ut es re pr es en te d t he m os t ab un da nt p hy lu m i n b ot h • N C s a nd A SD P Ts • ↑ Bac te ro ide te s/ Fir m ic ut es rat io • Fa m ily l ev el : ↓ Ac tin om yc et ac eae , Cor iobac te riac eae , Bi fidobac te riac eae , G em ell ac eae , a nd St re pt oco cc ac ea e • O bs er ve d a r ea ss or tm en t o f t he gu t e co sy st em i n y ou ng A SD P Ts • ↑ m uc in -d eg ra di ng R . t or qu es i n fe ce s o f A SD P Ts • ↑ bu ty rog eni c F. p ra us ni tz ii a nd bu ty ra te i n A SD p ts • A l im ite d n um be r o f evalu at ed c hi ldr en (Conti nue s)
Re fer en ce s Sa m ple s iz e M ea n a ge i n ye ar s ± SD (R an ge ) G en der (M ale / Female ) C ha ng es i n t ax on om ic c om po si tio n ( in PT c om pa re d t o N C ) A ss oc ia tio n w ith c lin ic al f ea tu re s ( in PT c om pa re d t o N C ) Li m ita tio ns /N ot es Z ha ng e t a l. (2 018 ) • A SD : 3 5 • N C : 6 • A SD : 4 .9 ± 1 .5 • N C : 4 .6 ± 1 .1 • A SD : ( 29 /6 ) • N C : ( 5/ 1) • Ph yl um l ev el : ↑ Ba cte ro id ete s/ Fir m ic ut es rat io • G en us l ev el : A r el at iv e ↑ o f Su tt er el la a nd O dor ibac te r a nd si gn ifi ca nt ↑ Bu ty ric im on as • ↓ Ve ill on ell a a nd St re pt oco cc us • ↓ B ut yr at e a nd l ac ta te p ro du ce rs • ↓ d iv er si ty • ↑ m uc in d eg ra de rs a nd o th er S C FA pr od uc er s • Re la tiv e ↓ m uc ol yt ic A kk er ma ns ia m uc ini ph ila b ac ter iu m • A bn or m al i nt es tin al p er m ea bi lit y ha s b ee n r ep or te d i n P Ts • A SD i s p os iti ve ly c or re la te d w ith pe rio do nt al , n eg at iv el y r el at ed t o ty pe 1 d ia be te s • ↑ D −A rg in in e a nd D −o rn ith in e m et ab ol is m , e th er l ip id m et ab ol is m , b ac te ria l c he m ot ax is , neu ro de ge ne ra tiv e di se ase s, p rio n di se ase s, p ho sp ho tr an sf er ase sy st em , a nd f la ge lla r a ss em bl y ge ne s i n P T g ro up • ↑ m ei os is -y ea st , s te ro id h or m on e bi os yn th es is , gl yc os ami no gl yc an de gr ad at io n, a nd l ip oi c a ci d m et ab ol is m i n t he N C g ro up • Sm al l s am pl e s ize • Th e h um an –m ic ro be di se as e a ss oc ia tio n da ta ba se u se d h as n ot be en u pd at ed s in ce i t w as es ta bl is he d St ra ti e t a l. (2 017 ) • A SD : 4 0 • N C : 4 0 • A SD : 1 0 ( 5– 17 ) • N C : 7 ( 3. 6– 12 ) • A SD : ( 31 /9 ) • N C : ( 28 /1 2) • ↑ Fir m ic ut es /B ac te ro ide te s r at io • G en us l ev el : ↓ Ali st ip es , B ilop hi la , D ia lis ter , P ar ab ac ter oi de s, a nd Ve ill on ell a • ↑ Co llin se lla , C or yn ebac te riu m , D ore a, a nd La ct obac illu s • *F un ga l a lte ra tio ns : g en us Cand id a w as o ne o f t he m os t a bu nd an t t ax a in t he g ut m yc ob io ta • C on st ip at io n h as a s ig ni fic an t ef fe ct o n t he m ic ro bi al c om m un ity w ith in N C s b ut n ot w ith in P Ts • Th e s ev er ity o f t he a ut is tic ph en ot yp e d oe s n ot a ff ec t t he ba ct er ia l c omm un ity NA In ou e e t a l. (2 016 ) • A SD : 6 • N C : 6 In fa nt s ( nu m be rs N A ) NA • G en us l ev el : ↑ Fa ec ali ba ct er iu m • ↓ Bl au tia Fa ec ali bac ter iu m a bu nd an ce w as st ro ng ly c or re la te d w ith a g re at er nu m be r o f d iff er en tia lly e xp re ss ed ge ne s i nv ol ve d i n b ot h t he inte rf er on- γ-m ed ia te d s ig na lin g pa th w ay a nd t he t yp e I i nt er fe ro n si gn al ing p at hwa y • Sm al l s am pl e s ize • N o s tr at ifi ca tio n f or a ge an d s ex T A B LE 1 (Co nti nue d) (Co nti nue s)
Re fer en ce s Sa m ple s iz e M ea n a ge i n ye ar s ± SD (R an ge ) G en der (M ale / Female ) C ha ng es i n t ax on om ic c om po si tio n ( in PT c om pa re d t o N C ) A ss oc ia tio n w ith c lin ic al f ea tu re s ( in PT c om pa re d t o N C ) Li m ita tio ns /N ot es To m ov a e t a l. (2 01 5) • A SD : 1 0 • Si bl in gs : 9 • N C : 1 0 • A SD : ( 2– 9) • Si bl in gs : ( 5– 17 ) • N C : ( 2– 11 ) • A SD : ( 9/ 1) • Si bl in gs : ( 7/ 2) • N C : 1 0 b oy s • ↓ Bac te ro ide te s/ Fir m ic ut es rat io • Ph yl um l ev el : N o d iff er en ce i n Ba cte ro id ete s o r Fir m ic ut es p hy la • G en us l ev el : ↓ Cl os tr id ia a nd D es ul fo vib rio • ↓ Bi fidobac te riu m in s ib lin gs t ha n i n A SD P Ts • A v er y s tr on g a ss oc ia tio n o f D es ul fo vib rio s pp . w ith t he s ev er ity of A SD • A s tr on g p os iti ve c or re la tio n o f A SD s ev er ity w ith t he s ev er ity o f G I d ys fu nc tio n. • N o c or re la tio n b et w ee n p la sm a le ve ls o f o xy to ci n, t es to st er on e, D H EA -S , a nd f ec al m ic ro bi ot a w er e • ↑ G I d ys fu nc tio n i n P Ts a s w el l a s in th eir s ib lin gs • B ac te ro id et es /F irm ic ut es r at io ha d a w ea k n eg at iv e c or re la tio n w ith t he s ev er ity o f A SD • ↓ L ev el o f o xy to ci n i n t he p la sm a of P Ts a nd t he ir s ib lin gs • Sm al l s am pl e s ize • N o s tr at ifi ca tio n f or a ge or s ex D e A ng el is et a l. ( 20 13 ) • A SD : 1 0 ot he r r el at ed di so rder s: 1 0 • N C : 1 0 (4 –1 0) In t ot al : ( 14 /1 6) • Fa ec ali ba ct er iu m a nd Rum in oc oc cu s w er e p re se nt a t t he h ig he st i n A SD • Cal or am at or , S arc in a, a nd Cl os tr id iu m w er e t he h ig he st i n A SD • Ex ce pt f or Eu bac te riu m sir ae um , th e l ow es t l ev el o f E ubac te riac eae w as f ou nd o n f ec al s am pl es o f A D chi ld re n. • Th e l ev el o f B ac te ro id ete s g en er a an d s om e Al is tip es a nd Ak ke rma ns ia sp ec ie s w er e a lm os t t he h ig he st i n A SD a nd r el at ed d is or de rs c hi ld re n • Su tt er el la cea e a nd En te robac te riac eae w er e h ig he r i n A SD • Bi fidobac te riu m s pec ies d ec re as ed in A SD NA • Sm al l s am pl e s ize • D em og ra ph ic d at a a re no t f ul ly d et ai le d f or e ac h su bgr ou p T A B LE 1 (Co nti nue d) (Co nti nue s)
Re fer en ce s Sa m ple s iz e M ea n a ge i n ye ar s ± SD (R an ge ) G en der (M ale / Female ) C ha ng es i n t ax on om ic c om po si tio n ( in PT c om pa re d t o N C ) A ss oc ia tio n w ith c lin ic al f ea tu re s ( in PT c om pa re d t o N C ) Li m ita tio ns /N ot es Fi ne go ld e t a l. (2 010 ) • A SD : 3 3 • si bl in gs : 7 • N C : 8 (2 –1 3) • A SD : ( 24 /9 ) • si bl in gs : ( 5/ 2) • N C : ( 5/ 3) • Phy lu m l ev el : B ac te ro id ete s w as fo un d a t h ig h l ev el s i n t he s ev er el y A SD P Ts , w hi le Fir m ic ut es w er e m or e p re do m in an t i n N C • Sm al le r b ut s ig ni fic an t d iff er en ce s in t he Ac tin obac te riu m a nd Pr ot eobac te riu m p hy la . • D es ul fo vib rio s pe ci es a nd Bac te ro ide s v ul ga tu s a re h ig he r i n A SD P Ts NA • Th e i m m un e s ta tu s w as no t i nv es tig at ed • Py ro se qu en ci ng i s l im ite d by n or m al p rim er b ia se s as w el l a s t he i nc om pl et e na tu re o f 1 6S r D N A da ta ba se s Pa rr ac ho e t a l. (2 00 5) • A SD : 5 8 • si bl in gs : 1 2 • N c:1 0 • A SD : ( 3– 16 ) • si bl in gs : ( 2– 10 ) • N C : ( 3– 12 ) • A SD : ( 48 /1 0) • si bl in gs : ( 7/ 5) • N C : ( 6/ 4) • Fe ca l f lo ra o f A SD P Ts c on ta in ed a hi gh er i nc id en ce o f t he Cl os tr id iu m hi st oly tic um g ro up ( C lo st rid iu m cl us te rs I a nd I I) b ut h ea lth y s ib lin g gr ou p d is pl ay ed i nt er m ed ia te l ev el s. • H ea lth y s ib lin g g ro up h ar bo re d t he lo w es t l ev el s o f B ac te ro ide s o f a ll th e s ub je ct g ro up s. • G I p ro bl em s w er e a ss oc ia te d w ith hi gh l ev el s o f C los tr id ia . • A n a ss oc ia tio n b et w ee n h ig h Cl os tr id ia l c ou nt s a nd i nd iv id ua ls co ns umin g pr obi ot ic s NA Sa nd le r e t a l. (2 000 ) A SD : 1 1 A SD : 5 9 ± 13 .3 ( in m on th s) A SD : (1 0/1 ) O nl y i n 4 A SD c hi ld re n: A na er ob ic co cc i, c hi ef ly pe pt os tre pt oco cc al sp ec ie s w er e a bs en t NA • Sm al l s am pl e s ize • N o c on tr ol s M in g e t a l. (2 018 ) • A D H D : 6 8 • N C : 72 • A D H D : 1 0. 3 ± 2. 97 • N C : 9 .7 ± 3 .2 4 • A D H D : ( 51 /1 7) • N C : ( 33 /3 9) G en us l ev el : S lig ht ↑ i n Bi fidobac te riu m • N o s ig ni fic an t r el at io ns hi p be tw ee n m ed ic at io n a nd co ns tip at io n, f la tu le nc e o r t ot al G as tr oi nt es tin al S ev er ity I nd ex • PT s h ad s ig ni fic an tly ↑ m ea n G as tr oi nt es tin al S ev er ity I nd ex , co ns tip at io n, a nd f la tu le nc e sc or es . NA Pr eh n-K ris ten sen et a l. ( 20 18 ) • A D H D : 1 4 • N C : 1 7 • A D H D : 1 1. 9 ± 2. 5 • N C : 1 3. 1 ± 1. 7 O nl y mal es • N o d iff er en ce i n t he o bs er ve d sp ec ie s a nd C ha o1 r ic hn es s es tim at or w hi le S ha nn on d iv er si ty w as s ig ni fic an tly ↓ . • G en us l ev el : P re vo te lla a nd Pa ra ba ct er oi de s w er e d et ec te d a s m ar ke rs f or t he N C s g ro up a nd N eisse ria fo r P Ts . • Fa m ily le ve l: ↑ Pr ev ot ell ac eae , Ca ta ba ct er iac eae , a nd Por ph yr om on ad ac eae fo r N C s a nd Ne iss eri ac ea e f or P Ts A c or re la tio n b et w ee n t he s ym pt om s of h yp er ac tiv ity a nd a lp ha d iv er si ty . • N o f em al e P Ts • 10 o ut o f 1 4 P Ts h ad ta ken me th yl ph en id at e • Sm al l s am pl e s ize T A B LE 1 (Co nti nue d) (Co nti nue s)
Re fer en ce s Sa m ple s iz e M ea n a ge i n ye ar s ± SD (R an ge ) G en der (M ale / Female ) C ha ng es i n t ax on om ic c om po si tio n ( in PT c om pa re d t o N C ) A ss oc ia tio n w ith c lin ic al f ea tu re s ( in PT c om pa re d t o N C ) Li m ita tio ns /N ot es A ar ts e t a l. (2 017 ) • Micr obi om e an al ys is • A D H D : 1 9 • N C : 7 7 • fM RI a na ly si s • A D H D : 2 4 • N C : 6 3 • O ve rla p • A D H D : 6 • N C : 2 2 • Micr obi om e an al ys is • A D H D : 1 9. 5 ± 2. 5 • N C : 2 7. 1 ± 14 .3 • fM RI a na ly si s • A D H D : 2 0. 3 ± 3. 7 • N C : 2 1. 3 ± 3. 4 • O ve rla p • A D H D : 1 8. 6 ± 2. 5 • N C : 2 1. 1 ± 3. 3 • Micr obi om e an al ys is • A D H D : ( 13 /6 ) • N C : ( 41 /3 6) • fM RI a na ly si s • A D H D : ( 18 /6 ) • N C : ( 39 /2 4) • O ve rla p • A D H D : ( 4/ 2) • N C : ( 13 /9 ) • Phy lu m l ev el : ↑ Ac tin obac te ria , ↓ Fir m ic ut es • G en us l ev el : ↑ Bi fidobac te riu m • O rder le ve l: ↓ Cl os tr id ia le s • Si gn ifi ca nt ↑ c yc lo he xa di en yl de hy dr at as e ( C D T) e nz ym e (in vo lv ed i n t he p ro du ct io n of p he ny la la ni ne , t yr os in e, o r tr yp to ph an ) • A n eg at iv e a ss oc ia tio n o f C D T w ith r ew ar d a nt ic ip at io n re sp on se s i n t he b ila te ra l v en tr al st riat um • Th e m ic ro bi om e s ho tg un se qu enc in g me tho d co uld ha ve b ee n c om bi ne d w ith a p ro te om ic s/ m et ab olo m ic s ap pr oa ch • 25 % o f N C s w er e s ib lin gs of A D H D c as es , a nd an ot he r s ub -s am pl e o f th e c on tr ol g ro up d id n ot un de rg o cl in ic al s cr ee nin g fo r A D H D • Th e N C s g ro up w as si gn ifi ca nt ly o ld er t ha n th e P T g ro up N gu ye n e t a l. (2 01 9) • SZ : 2 5 • N C : 2 5 • SZ : 5 2. 9 ± 11 .2 • N C : 5 4. 7 ± 10 .7 • SZ : ( 11 /1 4) • N C : ( 10 /1 5) • Phy lu m l ev el : ↓ Pr ot eobac te ria • G en us l ev el : ↑ An ae ro co cc us , ↓ H aem op hi lu s, Su tt er el la , a nd Cl os tr id iu m • ↑ D ep re ss iv e s ym pt om s w ith ↑ ge nu s Bac te ro ide s • ↑ N eg at iv e s ym pt om s w ith ↓f am ily R umi no co cc ac eae • M en ta l w el l-b ei ng w as p os iti ve ly co rr el at ed w ith p hy lu m Ver ru co mi cr ob ia • C ros s-se ct io na l • Sm al l s am pl e s ize • N ot c on si de rin g C om or bi d m edic al ill ne ss es Sh en e t a l. (2 018 ) • SZ : 6 4 • N C : 5 3 • SZ : 4 2 ± 11 • N C : 3 9 ± 14 • SZ : ( 36 /2 8) • N C : ( 35 /1 8) • Phy lu m l ev el : ↑ Pr ot eobac te ria , Fu sobac te ria • G en us l ev el : ↑ Su cci ni vi br io, M eg as phae ra , C oll in se lla , C los tr id iu m , Kl eb sie lla , a nd M et ha nob re vibac te r • ↓ B la ut ia , C op ro co cc us , a nd Ros eb ur ia Se ve ra l m et ab ol ic p at hw ay s d iff er ed si gn ifi ca nt ly : V ita m in B 6, f at ty a ci d, st ar ch a nd s uc ro se , t ry pt op ha n, cy st ei ne , m et hi on in e, a nd l in ol ei c ac id m et ab ol is m , a s w el l a s t he de gr ad at io n of s ome x eno bi ot ic s • C ros s-se ct io na l • Sm al l s am pl e s ize • Li m ite d p op ul at io n (C hi ne se H an n at io na lit y) • N ot c om pl et el y el imina tin g an tips ych ot ic s’ ef fe ct C as tr o-N all ar et a l. ( 20 15 ) • SZ : 1 6 • N C : 1 6 • SZ : 3 4. 7 ± 4. 8 • N C : 3 4. 3 ± 10 .1 • SZ : ( 9/ 7) • N C : ( 9/ 7) • Phy lu m l ev el : ↑ Fir m ic ut es , Ba cte ro id ete s, a nd Ac tin oba ct er ia • Spec ies le vel : ↓ s pe ci es n um be r • ↑ L ac tic a ci d b ac te ria : L ac tobac illu s ga sse ri w as 4 00 t im es m or e ab un da nt • ↑ St re pt oco cc us g or do ni i, St rep to co cc us th er m op hi lu s a nd • St re pt oco cc us sp . • ↑ S ev er al m et ab ol ic p at hw ay s: sa cc ha rid e, p ol yo l, a nd l ip id tr an sp or t s ys te m s, p ep tid e a nd ni ck el t ra ns po rt , m et al lic c at io n, iro n-si de ro ph or e, a nd v ita m in B1 2 t ra ns po rt a nd p ho sp ha te a nd am in o a ci d t ra ns po rt i nc lu di ng glu ta ma te tr an sp or t. • ↓ Se ve ra l m et ab ol ic p at hw ay s: en er gy , c ar bo hy dr at e a nd l ip id m et ab ol is m • A ll N C s w er e no n-sm ok er s. T A B LE 1 (Co nti nue d) (Co nti nue s)
Re fer en ce s Sa m ple s iz e M ea n a ge i n ye ar s ± SD (R an ge ) G en der (M ale / Female ) C ha ng es i n t ax on om ic c om po si tio n ( in PT c om pa re d t o N C ) A ss oc ia tio n w ith c lin ic al f ea tu re s ( in PT c om pa re d t o N C ) Li m ita tio ns /N ot es Yo lk en e t a l. (2 01 5) • SZ : 4 1 • N C : 3 3 • SZ : 3 9. 2 ± 9. 9 • N C : 3 0. 9 ± 8. 8 • SZ : ( 27 /1 4) • N C : ( 19 /1 4) Ph ia dh l ev el :↑ L ac toba ci llu s p ha ge ph iad h • Ph ia dh l ev el w as a ss oc ia te d w ith th e a dm in is tr at io n o f V al pr oa te • ↑ co m or bi d i m m un ol og ic al di so rd er s i n P Ts • Li m ite d s am pl e s ize s C oe llo e t a l. (2 01 9) • B D : 1 13 • U R: 3 9 • N C : 7 7 • B D : 3 1 ( 26 –3 9) • U R: 2 8 ( 22 – 34 ) • N C : 2 9 ( 24 .5– 40 .5 ) • B D : ( 43 /7 0) • U R: ( 18 /2 1) • N C : ( 30 /4 7) G en us l ev el : F la von ifr ac tor w as pr es en t i n 6 1% o f B D P Ts , 4 2% o f U R a nd 3 9% o f N C . I n B D P Ts , i t w as as so ci at ed w ith s m ok in g a nd f em al e sex • Fl av on ifr ac tor w hi ch m ay i nd uc e ox id at iv e s tr es s a nd i nf la m m at io n in i ts h os t w as a ss oc ia te d w ith B D . • C ros s-se ct io na l • Sm al l U R s am pl e s ize • Se lf-re po rt ed p hy si ca l ac tiv ity • N o d ie ta ry i nf or m at io n • N o i nf or m at io n o n bo w el m ov emen ts /s to ol co ns is te nc y A iz aw a e t a l. (2 01 9) • B D : 3 9 • N C : 5 8 • B D : 4 0. 3 ± 9. 2 • N C : 4 3. 1 ± 12 .9 • B D : ( 17 /2 2) • N C : ( 22 /3 6) • N o s ig ni fic an t d iff er en ce w as f ou nd in e ith er b ac te ria l c ou nt s b et w ee n th e t w o g ro up s • A s ig ni fic an t n eg at iv e c or re la tio n be tw ee n Lac tobac illu s c ou nt s a nd sl ee p ( p = 0. 01 ) • A s ig ni fic an t n eg at iv e c or re la tio n be tw ee n Bi fidobac te riu m b ut n ot Lac toba ci llu s c ou nt s a nd c or tis ol le ve ls ( p = 0. 02 ) i n B D P Ts • Bi fidoba ct er iu m o r L ac to bac illu s co un ts m ay no t p la y a m aj or ro le in th e p at ho ph ys io lo gy o f B D i n t hi s co ho rt • Po ss ib le r ol es o f t he se b ac te ria i n sl ee p a nd s tr es s r es po ns e o f t he B D P Ts • Th e s ev er ity o f B D i n t he su bj ec ts w as r el at iv el y m ild • N o d et ai le d c ou nt s of d iff er en t s pe ci es of Bi fidobac te riu m o r Lac tobac illu s • Th e c ro ss -s ec tio na l de si gn o f t he p re se nt st ud y m ak es i t d iff ic ul t t o de te rm ine w he the r t he obs er ve d re la tio ns hips w er e t he c au se s o r ef fe ct s o f t he i lln es s. Pa in ol d e t a l. (2 018 ) • B D : 3 2 • N C : 1 0 • B D : 4 1. 3 ± 14 .7 • N C : 3 1. 4 ± 7. 6 • B D : ( 18 /1 4) • N C : ( 4/ 6) • Phy lu m l ev el : ↑ A ct in obac te ria a nd Cor iobac te ria (c las s) • G en us l ev el : ↓ Ru mi no co cc ac eae a nd Fa ec ali ba ct er iu m • A n eg at iv e c or re la tio n b et w ee n micr obi al a lp ha -di ve rs ity a nd ill ne ss d ur at io n • Id en tif ie d b ac te ria l c la ss es as so ci at ed w ith i nf la m m at or y st at us , s er um l ip id s, T RP , dep re ss iv e sy m pt om s, o xi da tiv e st re ss , a nt hr op om et ric s, a nd m et ab ol ic s yn dr om e i n B D P Ts • C ros s-se ct io na l • Sm al l s am pl e s ize • A ll B D P Ts w er e i n a n ac ut e e pi so de o f b ip ol ar dep re ss io n. • N o e xp lic it a ss es sm en t/ st an da rd iz at io n o f d ie t/ lif es ty le pa ra m et er s T A B LE 1 (Co nti nue d) (Co nti nue s)
Re fer en ce s Sa m ple s iz e M ea n a ge i n ye ar s ± SD (R an ge ) G en der (M ale / Female ) C ha ng es i n t ax on om ic c om po si tio n ( in PT c om pa re d t o N C ) A ss oc ia tio n w ith c lin ic al f ea tu re s ( in PT c om pa re d t o N C ) Li m ita tio ns /N ot es Sc hw ar z e t a l. (2 018 ) FE P: 2 8 N C : 1 6 FE P: 2 5. 9 ± 5. 5 N C : 2 7. 1 ± 6.0 FE P: (1 6/1 2) N C : ( 8/ 8) • Fa m ily le ve l: ↑ Lac tobac ill ac eae , H al ot hi obac ill ac eae , B ruc ell ac eae a nd M ic ro co cci ne ae , ↓ Ve ill on ell ac eae • G en er a: ↑ Lac toba ci llu s, Tr op her ym a, H al ot hi obac illu s, S ac cha ro pha gu s, O ch robac tr um , D ef er ribac te r, and H al or ub rum , ↓ Ana ba ena , N itr os os pi ra a nd G all ion ell a Lac hn os pir ac eae , B ac te ro ide s s pp ., Lac toba ci llu s w er e c or re la te d w ith ↑ ps ych ot ic s ym pt om s • Sm al l s am pl e s ize • N o c om m un ity -le ve l ch ar ac ter is tic s rep or te d • A m od el p re di ct in g re m is si on o nl y u se d t he to p 5 f am ili es r at he r t ha n th e en tir e p opu la tio n Ev an s e t a l. (2 017 ) • B D : 1 15 • N C : 6 4 • B D : 5 0. 2 ± 12 .8 • N C : 4 8. 6 ± 16 .6 • B D : ( 32 /8 3) • N C : ( 24 /4 0) • G en us l ev el : ↓ Fa ec ali bac ter iu m • ↓ un cl as sif ie d (F am ily le ve l: Ru mi no co cc ac eae ) Fa ec ali bac ter iu m w as a ss oc ia te d w ith i m pr ov ed p hy si ca l h ea lth , de pr es si on , a nd s le ep q ua lit y sc or es ; A na er os tip es a nd Ru mi no co cc ac eae fa m ily w er e as so ci at ed w ith i m pr ov ed ph ys ic al h ea lth , w hi le a n un cl as si fie d g en us f ro m t he f am ily En te robac te riac eae w as a ss oc ia te d w ith w or se p hy si ca l h ea lth s co re s • C ros s-se ct io na l • In ab ili ty t o c on tr ol f or m ed ic at io n u se a nd co mp lia nc e Fl ow er s e t a l. (2 017 ) • B D o n A P: 4 6 • B D o ff A P: 6 9 • B D o n A P: 4 6. 0 ± 12 .0 • B D o ff A P: 5 1. 7 ± 13 .5 • B D o n A P: • (1 2/ 34 ) • B D o ff A P: • (2 1/ 48 ) • A P-tr ea te d P Ts : ↑ Lac hn os pir ac eae • N on -A P-tr ea te d P Ts : ↑ Ak ke rma ns ia an d Su tt er el la ↓ Ak ke rma ns ia in n on -o be se A P-tr ea te d P Ts • Ill ne ss ’ d ur at io n, d is ea se' s in di ca to rs , a nd s ym pt om se ve rit y w er e n ot co ns ider ed . • C om or bi d m ed ic al co nd iti on s/ ot he r m et ab ol ic b io m ar ke rs ef fe ct o n m ic ro bi om e ne ed ed f ur th er in ve st ig at io n. • N o d ie ta ry i nf or m at io n N ote : A ll s tu di es a re a rr an ge d i n a r ev er se d c hr on ol og ic al o rd er ( fr om t he n ew es t t o o ld es t) p er d ia gn os is . A bb re vi at io ns : ↑ i nd ic at es a n i nc re as e; ↓ i nd ic at es a d ec re as e; A D H D , a tt en tio n d ef ic it h yp er ac tiv ity d is or de r; A P, a nt ip sy ch ot ic s; A SD , a ut is m s pe ct ru m d is or de r; B D , b ip ol ar d is or de r; F EP , f irs t e pi so de pa tie nt s; G I, g as tr o-i nt es tin al ; N A , n ot a va ila bl e; N C , n on -n eu ro ps yc hi at ric c om pa ris on s ub je ct ; P T, p at ie nt ; S Z, s ch iz op hr en ia ; U R , u na ff ec te d f irs t d eg re e r el at iv e. T A B LE 1 (Co nti nue d)
the density of microglia, mostly in the temporal cortex, and on the molecular level an overall increase in expression of pro-inflammatory genes on both transcript and protein levels (van Kesteren et al., 2017) together with an increase in microglial markers (Barichello, Simoes, Quevedo, & Zhang, 2019). Interestingly, in live human subjects with SZ or BD, C4A mRNA expression in peripheral blood mononuclear cells predicts the presence and severity of delusions (Melbourne, Rosen, Feiner, & Sharma, 2018).
For ASD, the increase in brain volume in some children with ASD manifestations is frequently associated with excessive activation of microglia in regions with an overabundance of cortical neurons and connections (Morgan et al., 2010; Redcay & Courchesne, 2005; Sacco, Gabriele, & Persico, 2015; Suzuki et al., 2013; Walker et al., 2012). Genes associated with the functioning of microglia have shown higher expression levels in brain samples from patients with ASD in com-parison to controls (Parikshak et al., 2016), and gene co-expression network analysis of postmortem ASD brain tissue identified an upreg-ulation of glial markers in the cortex, along with a downregupreg-ulation of a module containing synaptic genes, compared with typically develop-ing individuals (Voineagu et al., 2011). Moreover, genes that regulate the development of microglia are more activated in males (Werling, Parikshak, & Geschwind, 2016) who suffer from ASD more frequently compared to females with a ratio of 4:1 (Fombonne, 2009; Gillberg, Cederlund, Lamberg, & Zeijlon, 2006). In addition, the DNA methyla-tion of genes known to be the modulators of the microglial activity or implicated in synaptic pruning has been found to be dysregulated in patients with ASD (Nardone et al., 2014; Prinz & Priller, 2014).
Autophagy also appears to be an essential component of microglia- mediated synaptic pruning (Plaza-Zabala, Sierra-Torre, & Sierra, 2017). Deletion of Atg7, an autophagy gene, specifically in microg-lia abolished its ability to prune synapses, resulting in an increase in dendritic spines with immature filopodia-like structures which may contribute to ASD pathogenesis by affecting the social behavior cir-cuit (Kim et al., 2017). Another study revealed that some children with ASD had overactive mTOR, a protein which prohibits the au-tophagy from cleaning the area and disposing of the damaged syn-apses (Tang et al., 2014). Immunohistochemical studies have shown that the brain tissue and cerebrospinal fluid samples from patients with ASD showed an abundance of activated microglia in the cerebral cortex, white matter, and cerebellum (Vargas, Nascimbene, Krishnan, Zimmerman, & Pardo, 2005). Furthermore, ASD postmortem brain tissues exhibited a decreased number of inactivated microglia in the grey and white matters and increased numbers of activated microglia in the grey matter (Lee, Azmitia, & Whitaker-Azmitia, 2017).
5 | THE LINK BETWEEN INTESTINAL
MICROBIOTA DYSBIOSIS AND MICROGLIAL
DYSFUNCTION IN NEUROPSYCHIATRIC
DISORDERS
The bidirectional communication between microbiota, the dif-ferent phyla and bacterial species in the GI system, and the brain
has drawn much attention in recent years. Several studies in mice showed significant effects of the different microbiota composi-tions on early life control of emocomposi-tions like anxiety, motor activity, and cognitive functions (Clarke et al., 2013; Desbonnet, Clarke, Shanahan, Dinan, & Cryan, 2014; Diaz Heijtz, 2016; Neufeld, Kang, Bienenstock, & Foster, 2011), confirming a functional connec-tion between the microbiota and brain. Studies mostly from the microbiota-devoid germ-free mice or mice treated with broad-spectrum antibiotics have shown that specific microbiota can impact brain physiology and neurochemistry and exhibit structural changes in the brain (Dinan & Cryan, 2017; Fung, Olson, & Hsiao, 2017; Martin & Mayer, 2017; Principi & Esposito, 2016; Zhang et al., 2015) and neurological deficiencies in learning, memory, recogni-tion, and emotional behaviors (Foster, Rinaman, & Cryan, 2017; Gareau et al., 2011; Smith, 2015), along with less social behaviors (Mayer, Tillisch, & Gupta, 2015; Schumann & Amaral, 2006; Vuong, Yano, Fung, & Hsiao, 2017).
In the general population, it is believed that brain development is influenced by the intestinal microbiota via several immunolog-ical and signaling pathways (for a review, see [Ma et al., 2019]). Moreover, the intestinal microbiota can modulate neurogenesis in the brain as demonstrated by the promotion of fetal neural develop-ment by some regulators from gut bacteria, which have a potential impact on cognitive function during adulthood (Humann et al., 2016; Rolls et al., 2007). The blood–brain barrier and vagus nerve actively participate in the bidirectional interactions between the intestinal microbiota and brain to maintain their homeostasis (Bonaz, Sinniger, & Pellissier, 2017; Braniste et al., 2014; Forsythe, Bienenstock, & Kunze, 2014).
Recently, the microbiota have shown an impact on the properties and function of microglia. For instance, with the absence of microbi-ota, microglia in germ-free mice displayed alteration in their morpho-logical characteristics and gene expression profiles, accompanied by inhibition in their maturation state in the brain cortex (Erny et al., 2015). This can indicate that the intestinal microbiota contribute di-rectly to the maturation progress of naïve microglia (Ma et al., 2019). In another study, it has been shown that microglia respond to micro-biota change in a sex- and time-dependent manner from prenatal stages (Thion et al., 2018). In a very recent study, the manipulation of microbiota in antibiotic-treated or germ-free adult mice resulted in significant deficits in fear extinction learning combined by an im-mature state and a change in gene expression in microglia (Chu et al., 2019). These microglial differentially expressed genes were found to be enriched in pathways related to synapse organization and syn-apse assembly, suggesting that deliberate manipulation of the mi-crobiota may alter microglia-mediated synaptic pruning and disrupt dendritic spine remodeling, causing behavioral abnormalities. By re-colonizing germ-free mice with a complete microbiota from healthy control mice immediately after birth, but not after weaning, the ex-tinction learning ability was restored, indicating that the exex-tinction learning and learning-related plasticity require microbiota-derived signals during a critical developmental period before weaning (Chu et al., 2019).
