Table 5.

Future recommendations.

Recommendations
1.Thorough and scientifically sound description of the patient population
a.Healthy volunteers and use of appropriate control groups	Despite good discriminative models between patients and HV, little is known about the VOC composition in HV and their natural evolution over time, the healthy human volatilome. Therefore, longitudinal prospective studies analysing VOCs in HV and patients will help determining a baseline healthy individual volatilome and map reproducibility.
b.Inclusion of cases that can interfere with differential diagnosis	To be able to accurately differentiate IBS and IBD, not only from each other but also from other gastrointestinal disorders, research should ideally include a broader range of gastrointestinal disorders in a case-control design to be able to compare results and to optimise specificity.
c.Dividing patients in disease subtypes	IBS and IBD patients are heterogeneous populations. Pooling data, therefore, is not advocated since it can distort results and important differences can be missed. IBS should ideally be classified according to the Rome IV criteria: diarrhoea, constipation, mixed and unspecified. The underlying pathophysiology is presumably different and different VOC patterns are thus to be expected. IBD patients should also be divided in CD and UC, and further subtyping in active disease and disease in remission could reveal interesting discriminatory characteristics. A proper sample size calculation should address the total number of patients to reveal subgroup characteristics.
2.Standardisation of the used methodology	The quality of the research included in this review, evaluated with the AXIS tool, is reasonable, but there is room for improvement in order to pinpoint relevant specific VOCs. Hence, to be able to compare results and cluster data, it is paramount for future research to perform proper sample size calculations, and achieve a high level of quality and standardisation, in composition of the research population, used research methods and sampling conditions. The European Respiratory Society has published guidelines concerning standardisation of breath analysis and future research should take this into account [61]. Differences in used technologies should be taken into account when comparing data. Interventional trials should ideally be organised as randomised placebo-controlled trials or cross-over trials.
3.Description of chemical denomination of the detected compounds allowing comparison between studies	Compounds should be described with the help of standardised international systems like the International union of pure and applied chemistry (IUPAC) nomenclature and numbers of the Chemical Abstracts Service (CAS). Compounds should ideally be verified using external standards and its concentration should be mentioned in studies for comparison.
4.Use of validation cohorts	The different models show very limited similarities, making comparison difficult. We stress the need for studies to split up patients and design models in a test set, and externally validating the discriminative models in independent patient validation groups in order to assess clinical utility. When validating results in different research facilities one should try to use the same technology and setup of the equipment. Another argument to promote validation is the limited sample size of some studies, since this could lead to overfitting of the data, leading to overoptimistic results.
5.Unravel the metabolic pathways involved	VOCs are formed by metabolic processes and influence other pathways. Analysis of VOCs and their underlying metabolic pathways could help explain the pathophysiological mechanisms causing IBS and IBD. Pathways and VOCs of interest could then be further analysed in in vivo models and animal research, potentially leading to detection and development of novel therapeutic targets. Short chain fatty acids are the group of compounds that stand out the most across all studies. Their role in inflammatory disorders is well documented so their presence in VOC analysis is not unexpected. A VOC compound of high interest is propan-1-ol, a part of the propanoate metabolism. It is mentioned in multiple articles looking into CD, it is found to be increased in CD patients compared to HV and IBS patients and, more importantly, it decreases after effective treatment, making propan-1-ol a compound with great potential as a discriminative VOC biomarker and also in predicting treatment effects of CD patients.
6.Match data of breath, faeces and urine analyses	Future studies should compare the VOC composition in breath, urine and faeces of the same patient which could give some insights into metabolic processes playing a role in disease and to elucidate the VOC metabolism from gut to breath.
7.Description of the environmental context and confounding factors
a.Environmental context	The surrounding air, called exposome, can majorly influence VOC composition. Therefore, it is crucial to take background samples and correct for possible external influences. The authors should ideally describe in detail how they corrected for differences in sample collection, sample handling, storage conditions and sample preparation.
b.Confounding factors	Patient factors can also influence results of VOC analysis, for example diet, exercise, and drugs. For instance, the FODMAP-diet influences the microbiota [17,68] and is frequently used to treat IBS and IBD patients. FODMAP carbohydrates are poorly digested and, as a consequence, are fermented by the colon microbiota leading to increased gas production and an osmotic effect in the bowel [17]. This indicates that the therapeutic effect of dietary interventions is heavily dependent on the composition of the microbiota of the patient [68]. For example, FODMAPs cause a decrease in Clostridium coccoides, Akkermansia muciniphila, Mycoplasma hominis, Bifidobacterium and Actinobacteria; and an increase in Ruminococcus torques[68]. The microbiota on the other hand produce metabolites through digestion of nutrients, which can have a direct or indirect effect on symptoms in IBS and IBD. Possible confounding factors should, therefore, be registered and taken into account when analysing data.