Systematic Review: The Gut Microbiome and Its Potential Clinical Application in Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a chronic relapsing–remitting systemic disease of the gastrointestinal tract. It is well established that the gut microbiome has a profound impact on IBD pathogenesis. Our aim was to systematically review the literature on the IBD gut microbiome and its usefulness to provide microbiome-based biomarkers. A systematic search of the online bibliographic database PubMed from inception to August 2020 with screening in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was conducted. One-hundred and forty-four papers were eligible for inclusion. There was a wide heterogeneity in microbiome analysis methods or experimental design. The IBD intestinal microbiome was generally characterized by reduced species richness and diversity, and lower temporal stability, while changes in the gut microbiome seemed to play a pivotal role in determining the onset of IBD. Multiple studies have identified certain microbial taxa that are enriched or depleted in IBD, including bacteria, fungi, viruses, and archaea. The two main features in this sense are the decrease in beneficial bacteria and the increase in pathogenic bacteria. Significant differences were also present between remission and relapse IBD status. Shifts in gut microbial community composition and abundance have proven to be valuable as diagnostic biomarkers. The gut microbiome plays a major role in IBD, yet studies need to go from casualty to causality. Longitudinal designs including newly diagnosed treatment-naïve patients are needed to provide insights into the role of microbes in the onset of intestinal inflammation. A better understanding of the human gut microbiome could provide innovative targets for diagnosis, prognosis, treatment and even cure of this relevant disease.


Introduction
The gastrointestinal microbiota comprises a collection of microbial communities, including viruses, bacteria, archaea and fungi, inhabiting the gastrointestinal tract [1]. The constitution and diversity of the microbiota in different sections of the gastrointestinal tract are highly variable and its concentration increases steadily along it, with small numbers in the stomach and very high concentrations in the colon [2,3]. This community has been linked to many diseases, including inflammatory bowel disease (IBD) [4].
IBD encompasses a group of chronic inflammatory bowel pathologies of idiopathic origin that affect millions of people throughout the world; the two most important pathologies covered by this term are Crohn's disease (CD) and ulcerative colitis (UC) [5]. IBD is not curable and shows a chronic evolution, with alternating periods of exacerbation and remission. This situation entails a high burden on health care systems, which try to provide treatment and to ensure quality of life for these complex patients who often require lifelong medical attention. Table 1. Gut microbiome studies in inflammatory bowel disease using non-next-generation sequencing approaches.

Study Design
Across the included studies, populations ranged from 2 to 531 patients, many of them with a small sample size that reduced the precision of the estimations. Thus, since many results are limited by sample size, further studies with larger cohorts are desirable to confirm these results and to clarify the significance of the microbiome in the pathogenesis of IBD.
In addition, to date, most published studies in IBD are cross-sectional (121 out of the 143 reviewed studies). However, longitudinal designs are required to capture changes that precede or coincide with disease and symptom onset, and to mechanistically relate microbiome shifts with disease pathogenesis. Overall, longitudinal studies in IBD (only 15% of the included studies) indicate that there is decreased stability in the microbiota composition in UC and CD patients [18,23,25,118,131,132,138,149]. These dynamic changes emphasize the importance of longitudinal sampling for a better understanding of taxa stability in individuals.
The IBD microbiome varies not only over time but also with treatment [80,155,156]. Newly diagnosed patients with no treatment provide an ideal scenario to study the potential etiopathogenesis related to intestinal dysbiosis that occurs in IBD. Mouse and human studies have proven that the gut microbiome is required for disease onset, as germ-free mice rarely develop the disease [157,158], antibiotics can prevent disease onset in mice [159] and ameliorate (but not cure) the disease in humans [160].
However, prior IBD microbiome studies have mostly included subjects with an established treatment; of the 143 microbiome studies included herein, only 11 included treatment-naïve patients [15,66,69,75,81,84,87,93,117,118,123], sometimes only on a small subset of the cohort, and only one was conducted prospectively.
Results on newly diagnosed treatment-naïve patients showed that gut dysbiosis is already established at the beginning of the disease. The dysbiotic profile in the gut of newly diagnosed treatment-naïve IBD patients presents reduced microbial abundance, less biodiversity in the structure of microbial communities, and differential bacterial abundances compared to the profile of established and treated IBD patients or control groups. Conversely, one study showed none or minor microbial differences between these patients and a control group [84].
Current knowledge, despite some controversy, provides valuable insights supporting the idea that microbial alterations may precede IBD onset. Given the limited number of studies in this type of patients, no consistent conclusion can be inferred, and further work is needed to investigate in depth the gut dysbiosis of newly diagnosed treatment-naïve IBD patients.

Microbiome Analysis Methods
Culture-independent and -dependent methods for microbial community analysis have both been used to describe microorganisms from different environments, including the human gut. However, due to the inability to culture the majority of the resident bacteria from the gastrointestinal tract, culture-independent methods have proven much more reliable and faster in profiling complex microbial communities.
Culture-independent techniques are based on sequence divergences of the small subunit ribosomal RNA (16S rRNA) or other target gene regions. Some of these techniques are quantitative real-time PCR (qPCR), denaturing gradient gel electrophoresis (DGGE), terminal restriction fragment length polymorphism (T-RFLP), fluorescence in situ hybridization (FISH), DNA microarrays, and NGS. All these techniques, except for NGS, are referred herein as non-NGS techniques.
Currently, there are many differences in study design and methodology among studies, making translation of basic science results into clinical practice a challenging task. Among the studies included in this review, very few used culture-dependent techniques (7 out of 143); and over the years, NGS became the most employed technique-79 studies used NGS, while 64 studies used non-NGS approaches.
Lately, the most widely used approaches are amplicon gene sequencing, predominantly the 16S rRNA gene (16S rDNA), and whole-genome shotgun sequencing, both NGS techniques.
Another recent technique much less used in this field is flow cytometry. A recent study demonstrated that cytometry fingerprints can be used as a diagnostic tool to classify samples according to CD state [154]. These results highlight the potential of flow cytometry as a tool to conduct rapid and cheaper diagnostics of microbiome-associated diseases.

Sample Type and Site
Currently, bacterial diversity in the human gut is determined through analysis of the luminal content (stool) and mucosal biopsies; however, the stool microbiome differs from the mucosa-associated microbiome [161]. Most of the bacteria are tightly adhered to the mucus and this mucosa-adhered microbiota may be associated with the pathogenesis of the disease [9,76]. Changes observed in stool samples likely represent an indirect measure of what is happening at the mucosal surface, where microorganisms interact more intimately with the host and induce disease.
The studies reviewed herein used fecal data, biopsy data or both, and most of them showed differences between fecal and biopsy samples [13,32,47,80,89,93,96,130], although a few studies found similarities [52,76]. The reported differences in microbial composition related to whether the sample origin was fecal or mucosal indicate that each biological sample represents a different environment thus emphasizing the importance of experimental design. Biopsies are primarily recommended for the dissection of the complex pathogenesis of IBD, whereas feces could effectively detect key biomarkers, enabling non-invasive continuous disease monitoring.
In biopsy samples, sampling site can also be a confounding factor. Many studies have compared the microbiome of inflamed and non-inflamed tissue from the same IBD patient. Regarding the effect of gut inflammation on the microbiota, there are some discrepancies among studies. Some researchers did not find significant differences in the mucosa-associated bacteria between apparently normal and inflamed mucosa in IBD patients [15,66,100,127,128,147]. Conversely, other studies found gut microbiome differences between inflamed and non-inflamed regions in mucosal biopsies [19,44,72,78,120,125,134,144]. This difference was also observed in fungal communities of inflamed mucosa, which are distinguishable from those of the non-inflamed area [63].
In spite of the controversial results, there is evidence supporting that inflamed and non-inflamed tissue samples in both CD and UC may present some differential microbiota composition suggesting that a comparison of mucosal samples obtained from identical sites in IBD patients and non-IBD controls is needed to avoid the confounding effect of inflammation in the assessment of the microbial profile.

Structural and Functional Analysis
IBD microbiome studies have typically focused on characterizing the composition of a community and less attention has been paid to functional profiles of the microbes within a community. Functional information can be inferred from the taxa through bioinformatic approaches or directly assessed via whole-genome shotgun sequencing.
Function is more informative than taxonomy [162] as it provides information on possible mechanisms acting on microbes and on microbe-host interactions, which are important for understanding microbial communities, specially microbiome-related diseases. The loss of a particular function could be more biologically meaningful than the loss of a single or a group of species.
The vast majority of the studies published on the IBD microbiome to date have focused on taxonomy and the reported associations in the IBD gut microbiome are largely limited to identifying high-level taxonomic classification (ranging from phyla to genera) given, for example, the limitations of amplicon gene sequencing for reliable species identification.
Some IBD gut microbiome studies have assessed the change in microbial function compared to healthy subjects. Outcomes of such studies showed a quite distinct change in microbial functions, such as fecal tryptic activity, oxidative response or lipid and glycan metabolism pathways [52,80,83,88,132]. Based on these results, it is necessary to redirect the study of dysbiosis from a purely compositional definition to a definition that includes functional changes of the microbiota.

Dysbiosis in IBD
The microbiome is different among healthy individuals around the globe [163], and the great differences found between the microbiomes of apparently healthy people complicate the definition of a healthy microbiome. Despite this divergence, the vast and diverse microbial gut community lives in relative balance in healthy individuals. Dysbiosis refers to an imbalance in microbial species, which is commonly associated with impaired gut barrier function and inflammatory activity [164]. It encompasses major traits such as loss of beneficial microbes, expansion of pathobionts, and loss of diversity [3] (Figure 1). The following sections will describe the key alterations found in the gut of IBD patients.
Microorganisms 2021, 9, x FOR PEER REVIEW 33 of 46 limited to identifying high-level taxonomic classification (ranging from phyla to genera) given, for example, the limitations of amplicon gene sequencing for reliable species identification. Some IBD gut microbiome studies have assessed the change in microbial function compared to healthy subjects. Outcomes of such studies showed a quite distinct change in microbial functions, such as fecal tryptic activity, oxidative response or lipid and glycan metabolism pathways [52,80,83,88,132]. Based on these results, it is necessary to redirect the study of dysbiosis from a purely compositional definition to a definition that includes functional changes of the microbiota.

Dysbiosis in IBD
The microbiome is different among healthy individuals around the globe [163], and the great differences found between the microbiomes of apparently healthy people complicate the definition of a healthy microbiome. Despite this divergence, the vast and diverse microbial gut community lives in relative balance in healthy individuals. Dysbiosis refers to an imbalance in microbial species, which is commonly associated with impaired gut barrier function and inflammatory activity [164]. It encompasses major traits such as loss of beneficial microbes, expansion of pathobionts, and loss of diversity [3] (Figure 1). The following sections will describe the key alterations found in the gut of IBD patients.

Defining the Gut Microbiome in IBD
Although the gastrointestinal tract contains trillions of resident microorganisms that include bacteria, archaea, fungi and viruses, the studies revised herein highlighted that current research on microbiome is mainly focused on bacteria.

Bacterial Dysbiosis
It has consistently been shown that there is a disease-dependent restriction of biodiversity and an imbalanced bacterial composition associated with IBD. The abundance of

Defining the Gut Microbiome in IBD
Although the gastrointestinal tract contains trillions of resident microorganisms that include bacteria, archaea, fungi and viruses, the studies revised herein highlighted that current research on microbiome is mainly focused on bacteria.

Bacterial Dysbiosis
It has consistently been shown that there is a disease-dependent restriction of biodiversity and an imbalanced bacterial composition associated with IBD. The abundance of beneficial microorganisms such as Clostridium groups IV and XIVa, Bacteroides, Suterella, Roseburia, Bifidobacterium species and Faecalibacterium prausnitzii is reduced, whereas some pathogens such as Proteobacteria members (including invasive and adherent Escherichia coli), Veil-lonellaceae, Pasteurellaceae, Fusobacterium species, and Ruminococcus gnavus are increased [4]. Most of the studies have revealed that in IBD patients, commensal bacteria are depleted and the microbial community is less diverse [14,22,37,48,80,94,106,108,126,143,150,152,153].
In the Firmicutes phylum, F. prausnitzii, an anti-inflammatory commensal bacterium, is frequently decreased in CD, while less evidence has been reported in UC, where it is sometimes increased and in other studies decreased [14,22,51,59,73,89,109,140,142,166,167]. Specific decrease in Roseburia spp. in patients with IBD has also been consistently noted [56,59,76,99,115,116,130]. Both bacteria are known to be involved in the production of butyrate, an important energy source for intestinal epithelial cells, which strengthens gut barrier function and exerts important immunomodulatory functions [168]. In this same phylum, the mucin degrader R. gnavus is frequently increased in IBD patients' gut, which may impair barrier stability and contribute to inflammation [38,76,103,111,116,132,140,144].

Fungal Dysbiosis
Despite the large body of literature on the IBD gut bacterial microbiome, little has been published on the gut mycobiome; specifically, only nine studies reviewed herein included fungal analysis.
Fungi are ubiquitous and their presence in the gastrointestinal tract has been demonstrated [169]. It was already evidenced many years ago that antibodies directed against mannoproteins of Saccharomyces cerevisiae (ASCA) were associated with CD, suggesting an inappropriate immune response to fungi in these patients [170].
Although fungi only constitute approximately 0.1% of the total microbial community in the gut [171], changes in gut mycobiota have been reported in IBD patients. However, results on fungal diversity are controversial; compared to controls, some studies have shown that fungal diversity is decreased in UC patients [107,112], and in CD, diversity and richness have been reported to be either increased [24,63], reduced [103,133], or unchanged [101]. Findings across fungal studies have consistently shown an increase in fungal load, especially in Candida albicans [24,63,101,102,107,133].
Nowadays, the exact mechanisms of intestinal fungi in IBD remain unclear and microbiome studies need to include fungi to properly address the complex challenges of this promising field.

Viral Dysbiosis
The human gut virome includes a diverse collection of viruses, mostly bacteriophages, directly impacting on human health [172]. In this systematic review, only seven studies included viral analysis [87,90,93,95,129,132,136]. Alterations in IBD gut virome showed an expansion of Caudovirales and an inverse correlation between the virome and bacterial microbiome, suggesting an hypothesis where changes in the gut virome may affect bacterial dysbiosis [90,95,129,136]. The use of data on both bacteriome and virome composition would contribute to improve classification between health and disease.
These findings suggest that the loss of virus-bacterium relationships can cause microbiota dysbiosis and intestinal inflammation. However, whether viruses have a direct role in IBD pathogenesis, or merely reflect underlying dysbiosis remains to be determined.

Archaeal Dysbiosis
The human gut microbiota also contains prokaryotes of the domain Archaea. Methaneproducing archaea (methanogens) have been associated with disorders of the gastrointestinal tract and dysbiosis. Methanogens play an important role in digestion, improving polysaccharide fermentation by preventing accumulation of acids, reaction end-products and hydrogen gas [173].
The two reviewed studies including archaeal analysis have shown that the variable prevalence of methanogens in different individuals may play an important role on IBD pathogenesis [61,71]. Lecours et al. showed that the abundance of Methanosphaera stastmanae in fecal samples was significantly higher in IBD patients than in healthy subjects. Interestingly, only IBD patients developed a significant anti-Msp. stadtmanae immunoglobulin G response, indicating that the composition of archaeal microbiome appears to be an important determinant of the presence or absence of autoimmunity [61].
The other study demonstrated an inverse association between Methanobrevibacter smithii load and susceptibility to IBD, which could be extended to IBD patients in remission as they found that Mbb. smithii load was markedly higher in healthy subjects compared to IBD patients [71].
Although archaeal diversity in the gastrointestinal tract is far lower than that of bacteria, these microorganisms can also exert inflammatory effects and their consideration in microbiome studies may be crucial for developing optimal diagnostics and prognostics tools.

Disease Activity and Severity
Different disease activity and severity have been described among IBD patients with a given clinically defined condition, suggesting that, in the context of microbiome dysfunction, each condition may present different microbial profiles. The reviewed studies showed a clear difference in the gut microbiota associated with different disease activity and severity in IBD patients.
Dysbiosis was evidenced by Tong et al. [83] at remission, where highly preserved microbial groups accurately classified IBD status during disease quiescence, suggesting that microbial dysbiosis in IBD may be an underlying disorder not only associated with active disease. In general, compared to inactive disease, bacterial diversity and richness are reduced in active disease. Studies of intestinal microbiota in active/inactive IBD patients have consistently shown an increase in F. prausnitzii and Clostridiales in inactive IBD compared to active IBD, and the increase in Proteobacteria in active IBD compared to inactive IBD. Besides, F. prausnitzii and R. hominis display an inverse correlation with disease activity [51,54,56,59,60,68,114,135,137,139,149].
Some studies showed that the genus Bifidobacterium is significantly decreased in stool samples during the active phase of CD and UC compared to the remission phase [43,49,68]. On the contrary, biopsies showed a higher abundance of Bifidobacterium during active UC, and the proportion of Bifidobacterium was significantly higher in biopsies than in the fecal samples in active CD patients [60]. Some controversial results were also found as other researchers did not find a correlation between microbiota and disease actitivity [35,45,50,101,105,138].
Regarding IBD severity, different microbial abundance was detected in both biopsies and fecal samples from patients with more aggressive disease, and gut dysbiosis was not only related to current activity but also to the course of the disease. In biopsies, Firmicutes showed a significant decrease and Proteobacteria a significant increase in more aggressive CD [135], and Bifidobacterium was inversely correlated with IBD severity [54,135,149]. The risk of flare was associated with reduced microbial richness, increased dysbiosis index and higher individualized microbial instability [74,122,132,137,146,153].
This area is still in its infancy and some results are inconsistent between studies. Several studies have evidenced microbiota signatures of disease activity and severity and the likelihood of a flare-up. However, more research is necessary to identify specific microbial taxa.

Gut Microbiome-Based Biomarkers in IBD
Ideal biomarkers should be easy to obtain, easy to determine, non-invasive, cheap, and capable of providing rapid and reproducible results. Non-invasive tests for IBD are already available, including serum antibodies [174,175], imaging-based screenings [176], and fecal biomarkers [177]. However, endoscopy remains the gold standard for IBD diagnosis, as the aforementioned non-invasive tests are limited to active disease and their outcome can be interfered by diseases other than IBD limiting their clinical utility.
As a non-invasive, cost-effective technique, microbiome-based biomarkers might have great potential for early-stage disease detection and disease course prognosis as well as for treatment based on patient stratification. To this end, several attempts have been made to develop indices of dysbiosis based on relative abundances of selected microbial taxa in IBD patients compared to those of a healthy population. In stool samples, a machine learning algorithm using a combination of 50 operational taxonomic units was able to differentiate remission from active CD [178], and the genera Collinsella and Methanobrevibacter could be used to differentiate between UC and CD [109]. In biopsies, Faecalibacteria and Papillibacter were indicators of IBD status [98], F. prausnitzii and E. coli were used for differential diagnosis of CD (ileal/colonic) [30], supervised learning classification models were able to classify IBD at specific intestinal locations [65], and microbiome shifts predicted patient outcome [62,64,132,137,145,154]. In biopsies, stool and blood a dysbiosis score accurately stratified IBD patients [132].
In the previous sections, differential results on the gut microbiome between CD and UC, IBD and healthy subjects or between different disease activities have been described. Such research on the IBD microbiome has evidenced that (1) alterations in the abundance of certain microbial taxa or (2) in the structure of the microbial community, (3) the decreased bacterial richness and/or diversity and (4) the decreased microbial community stability could be used as potential biomarkers in the field.
Nevertheless, due to the high microbiome diversity between individuals, and within the same individual over time, the predictive value of these potential indicators is currently far below the level required for utility in diagnosis, prognosis, or response to treatment. Nonetheless, the increasing number of microbiome studies along with the use of longitudinal approaches pave the way to the refinement of microbiome-based biomarkers as useful disease indicators.

Concluding Remarks and Future Perspectives
The study of the human microbiome and its involvement in human health is nowadays one of the most active research topics in biomedicine. A simple search for "Microbiota" and "disease" within PubMed Database reveals almost 28,000 hits to date (august 2020). Given the potential clinical application of the microbiome, the number of studies in this field is rapidly increasing. However, some limitations can be found across these studies, including different methodologic approaches, small cohort sizes, different microbiome analysis methods and sample types and sites, main focus on bacteria, and influence of disease activity and treatment interventions. Therefore, these limitations result in variable findings, difficulty to establish comparison between studies and lack of reproducibility of microbiome signatures across studies.
Recent studies based on novel DNA sequencing methods have revealed major differences in microbial taxonomic and functional composition between IBD patients and healthy individuals. The current knowledge guides us to move our focus from community composition to the understanding of the interactions between microbial functions and the IBD gut microbiome.
The microbiota is very specific to an individual and variable in time, and therefore studies need to go from searching for correlation to searching for causation through longitudinal approaches. One important factor that we must keep in mind when studying the microbiome is that it is a "living entity" subject to variability. This variability is even more evident in the IBD microbiome. To better understand the IBD-microbiome connection, we require prospective longitudinal studies, along with following populations with early-onset IBD. The question of whether dysbiosis precedes the development of IBD and sets the inflammatory process, or merely reflects the altered immune and metabolic environment of the inflamed mucosa, remains to be answered. For this reason, it is of paramount importance to study newly diagnosed treatment-naïve patients, where the microbiome can be studied at the beginning of the disease and without the influence of any IBD treatment. Developing unified approaches to the accurate quantitative assessment of the gut microbiome would contribute to comparisons among studies and to its further clinical application.
The main feature in IBD gut dysbiosis is the decrease in beneficial bacteria and the increase in pathogens. Gut microbiome studies are mainly focused on bacteria, yet beyond bacteria, the gut microbiome is composed of other microorganisms such as viruses, fungi or archaea, which play a role in IBD etiology and/or in bacterial population control. In addition, it is currently known that disease activity and severity influence the gut microbiome, thereby affecting the results. IBD can be considered as a "multimicrobial" disease with no single causative microorganism, in which more severe disease is linked to reduced gut microbial diversity, and proliferation or reduction in specific taxa. Therefore, future studies should include the whole community for a deeper understanding of this disease.
The usefulness of the gut microbiome as a tool towards targeted non-invasive biomarkers for IBD has been evaluated by compelling studies. An acceptable biomarker may help in early diagnosis and classification of IBD as well as in the prediction of disease outcome. Overall, IBD clinical management would benefit from the identification of microbiomebased biomarkers, which could provide less invasive assessment tools, enable personalized treatments, and reduce the health care economic burden associated with IBD. Collectively, these microbiome data represent a valuable data source that can be continually mined to identify associations between the microbiome and IBD for a deeper pathophysiological understanding which may promote the development of clinical strategies, including disease prevention, treatment, stratification and assessment of high-risk population.  Data Availability Statement: All data used, generated or analyzed during this study are included in this published article.

Conflicts of Interest:
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Identify the report as a systematic review, meta-analysis, or both. 1

Structured summary 2
Provide a structured summary including, as applicable: background; objectives; data sources; study eligibility criteria, participants, and interventions; study appraisal and synthesis methods; results; limitations; conclusions and implications of key findings; systematic review registration number.

Rationale 3
Describe the rationale for the review in the context of what is already known. 1-2

Objectives 4
Provide an explicit statement of questions being addressed with reference to participants, interventions, comparisons, outcomes, and study design (PICOS). 2

Protocol and registration 5
Indicate if a review protocol exists, if and where it can be accessed (e.g., Web address), and, if available, provide registration information including registration number. Specify study characteristics (e.g., PICOS, length of follow-up) and report characteristics (e.g., years considered, language, publication status) used as criteria for eligibility, giving rationale.

2
Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with study authors to identify additional studies) in the search and date last searched. 2 Search 8 Present full electronic search strategy for at least one database, including any limits used, such that it could be repeated. 2 Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic review, and, if applicable, included in the meta-analysis). 2 Data collection process 10 Describe method of data extraction from reports (e.g., piloted forms, independently, in duplicate) and any processes for obtaining and confirming data from investigators. 2 Section/topic # Checklist item Reported on page #

Data items 11
List and define all variables for which data were sought (e.g., PICOS, funding sources) and any assumptions and simplifications made. N/A

Risk of bias in individual studies 12
Describe methods used for assessing risk of bias of individual studies (including specification of whether this was done at the study or outcome level), and how this information is to be used in any data synthesis.

Summary of evidence 24
Summarize the main findings including the strength of evidence for each main outcome; consider their relevance to key groups (e.g., healthcare providers, users, and policy makers).

Limitations 25
Discuss limitations at study and outcome level (e.g., risk of bias), and at review-level (e.g., incomplete retrieval of identified research, reporting bias). N/A

Conclusions 26
Provide a general interpretation of the results in the context of other evidence, and implications for future research. 8-9

Funding 27
Describe sources of funding for the systematic review and other support (e.g., supply of data); role of funders for the systematic review. 9