Diagnosing Inflammatory bowel disease using noninvasive applications of volatile organic compounds: a systematic review

Optimized breath analysis: customized analytical methods and enhanced workflow for broader detection of VOCs

INTRODUCTION

Breath Volatile organic compounds (VOCs) are promising biomarkers for clinical purposes due to their unique properties. Translation of VOC biomarkers into the clinic depends on identification and validation: a challenge requiring collaboration, well-established protocols, and cross-comparison of data. Previously, we developed a breath collection and analysis method, resulting in 148 breath-borne VOCs identified.

OBJECTIVES

To develop a complementary analytical method for the detection and identification of additional VOCs from breath. To develop and implement upgrades to the methodology for identifying features determined to be "on-breath" by comparing breath samples against paired background samples applying three metrics: standard deviation, paired t-test, and receiver-operating-characteristic (ROC) curve.

METHODS

A thermal desorption (TD)-gas chromatography (GC)-mass spectrometry (MS)-based analytical method utilizing a PEG phase GC column was developed for the detection of biologically relevant VOCs. The multi-step VOC identification methodology was upgraded through several developments: candidate VOC grouping schema, ion abundance correlation based spectral library creation approach, hybrid alkane-FAMES retention indexing, relative retention time matching, along with additional quality checks. In combination, these updates enable highly accurate identification of breath-borne VOCs, both on spectral and retention axes.

RESULTS

A total of 621 features were statistically determined as on-breath by at least one metric (standard deviation, paired t-test, or ROC). A total of 38 on-breath VOCs were able to be confidently identified from comparison to chemical standards.

CONCLUSION

The total confirmed on-breath VOCs is now 186. We present an updated methodology for high-confidence VOC identification, and a new set of VOCs commonly found on-breath.

Rapid detection of depression by volatile organic compounds from exhalation

Depression is a pervasive and often undetected mental health condition, which poses significant challenges for early diagnosis due to its silent and subtle nature. To evaluate exhaled volatile organic compounds (VOCs) as non-invasive biomarkers for the detection of depression using a virtual surface acoustic wave sensors array (VSAW-SA). A total of 245 participants were recruited from the Hangzhou Community Health Service Center, including 38 individuals diagnosed with depression and 207 control subjects. Breath samples were collected from all participants and subjected to analysis using VSAW-SA. Univariate and multivariate analyses were employed to assess the relationship between VOCs and depression. The findings revealed that the responses of virtual sensor ID 14, 44, 59, and 176, which corresponded respectively to ethanol, trichloroethylene or isoleucine, octanoic acid or lysine, and an unidentified compound, were sensitive to depression. Taking into account potential confounders, these sensor responses were utilized to calculate a depression detection indicator. It has a sensitivity of 81.6% and a specificity of 81.6%, with an area under the curve of 0.870 (95% CI = 0.816-0.923). Conclusions: exhaled VOCs as non-invasive biomarkers of depression could be detected by a VSAW-SA. Large-scale cohort studies should be conducted to confirm the potential ability of the VSAW-SA to diagnose depression.

Delayed diagnosis in inflammatory bowel disease: Time to consider solutions

In this editorial, we discuss a recently published manuscript by Blüthner et al in the World Journal of Gastroenterology, with a specific focus on the delayed diagnosis of inflammatory bowel disease (IBD). IBD, which includes Crohn's disease and ulcerative colitis, is a chronic intestinal disorder. A time lag may exist between the onset of inflammation and the appearance of signs and symptoms, potentially leading to an incorrect or delayed diagnosis, a situation referred to as the delayed diagnosis of IBD. Early diagnosis is crucial for effective patient treatment and prognosis, yet delayed diagnosis remains common. The reasons for delayed diagnosis of IBD are numerous and not yet fully understood. One key factor is the nonspecific nature of IBD symptoms, which can easily be mistaken for other conditions. Additionally, the lack of specific diagnostic methods for IBD contributes to these delays. Delayed diagnosis of IBD can result in numerous adverse consequences, including increased intestinal damage, fibrosis, a higher risk of colorectal cancer, and a decrease in the quality of life of the patient. Therefore, it is essential to diagnose IBD promptly by raising physician awareness, enhancing patient education, and developing new diagnostic methods.

The breath volatilome is shaped by the gut microbiota

The gut microbiota is widely implicated in host health and disease, inspiring translational efforts to implement our growing body of knowledge in clinical settings. However, the need to characterize gut microbiota by its genomic content limits the feasibility of rapid, point-of-care diagnostics. The microbiota produces a diverse array of xenobiotic metabolites that disseminate into tissues, including volatile organic compounds (VOCs) that may be excreted in breath. We hypothesize that breath contains gut microbe-derived VOCs that inform the composition and metabolic state of the microbiota. To explore this idea, we compared the breath volatilome and fecal gut microbiomes of 27 healthy children and found that breath VOC composition is correlated with gut microbiomes. To experimentally interrogate this finding, we devised a method for capturing exhaled breath from gnotobiotic mice. Breath volatiles are then profiled by gas-chromatography mass-spectrometry (GC-MS). Using this novel methodology, we found that the murine breath profile is markedly shaped by the composition of the gut microbiota. We also find that VOCs produced by gut microbes in pure culture can be identified in vivo in the breath of mice monocolonized with the same bacteria. Altogether, our studies identify microbe-derived VOCs excreted in breath and support a mechanism by which gut bacterial metabolism directly contributes to the mammalian breath VOC profiles.

Update of gut gas metabolism in ulcerative colitis

INTRODUCTION

Ulcerative colitis (UC) is a chronic, nonspecific inflammatory disease of the intestine. The intestinal microbiota is essential in the occurrence and development of UC. Gut gases are produced via bacterial fermentation or chemical interactions, which can reveal altered intestinal microbiota, abnormal cellular metabolism, and inflammation responses. Recent studies have demonstrated that UC patients have an altered gut gas metabolism.

AREAS COVERED

In this review, we integrate gut gas metabolism advances in UC and discuss intestinal gases' clinical values as new biomarkers or therapeutic targets for UC, providing the foundation for further research. Literature regarding gut gas metabolism and its significance in UC from inception to October 2023 was searched on the MEDLINE database and references from relevant articles were investigated.

EXPERT OPINION

Depending on their type, concentration, and volume, gut gases can induce or alleviate clinical symptoms and regulate intestinal motility, inflammatory responses, immune function, and oxidative stress, significantly impacting UC. Gut gases may function as new biomarkers and provide potential diagnostic or therapeutic targets for UC.

Artificially Intelligent Olfaction for Fast and Noninvasive Diagnosis of Bladder Cancer from Urine

Globally, bladder cancer (BLC) is one of the most common cancers and has a high recurrence and mortality rate. Current clinical diagnostic approaches are either invasive or inaccurate. Here, we report on a cost-efficient, artificially intelligent chemiresistive sensor array made of polyaniline (PANI) derivatives that can noninvasively diagnose BLC at an early stage and maintain postoperative surveillance through ″smelling″ clinical urine samples at room temperature. In clinical trials, 18 healthy controls and 76 BLC patients (60 and 16 at early and advanced stages, respectively) are assessed by the artificial olfactory system. With the assistance of a support vector machine (SVM), very high sensitivity and accuracy from healthy controls are achieved, exceeding those obtained by the current techniques in practice. In addition, the recurrences of both early and advanced stages are diagnosed well, with the effect of confounding factors on the performance of the artificial olfactory system found to have a negligible influence on the diagnostic performance. Overall, this study contributes a novel, noninvasive, easy-to-use, inexpensive, real-time, accurate method for urine disease diagnosis, which can be useful for personalized care/diagnosis and postoperative surveillance, resulting in saving more lives.

Volatile compounds in human breath: critical review and meta-analysis

Volatile compounds contained in human breath reflect the inner workings of the body. A large number of studies have been published that link individual components of breath to disease, but diagnostic applications remain limited, in part due to inconsistent and conflicting identification of breath biomarkers. New approaches are therefore required to identify effective biomarker targets. Here, volatile organic compounds have been identified in the literature from four metabolically and physiologically distinct diseases and grouped into chemical functional groups (e.g. - methylated hydrocarbons or aldehydes; based on known metabolic and enzymatic pathways) to support biomarker discovery and provide new insight on existing data. Using this functional grouping approach, principal component analysis doubled explanatory capacity from 19.1% to 38% relative to single individual compound approaches. Random forest and linear discriminant analysis reveal 93% classification accuracy for cancer. This review and meta-analysis provides insight for future research design by identifying volatile functional groups associated with disease. By incorporating our understanding of the complexities of the human body, along with accounting for variability in methodological and analytical approaches, this work demonstrates that a suite of targeted, functional volatile biomarkers, rather than individual biomarker compounds, will improve accuracy and success in diagnostic research and application.

Volatolomics in healthcare and its advanced detection technology

Various diseases increasingly challenge the health status and life quality of human beings. Volatolome emitted from patients has been considered as a potential family of markers, volatolomics, for diagnosis/screening. There are two fundamental issues of volatolomics in healthcare. On one hand, the solid relationship between the volatolome and specific diseases needs to be clarified and verified. On the other hand, effective methods should be explored for the precise detection of volatolome. Several comprehensive review articles had been published in this field. However, a timely and systematical summary and elaboration is still desired. In this review article, the research methodology of volatolomics in healthcare is critically considered and given out, at first. Then, the sets of volatolome according to specific diseases through different body sources and the analytical instruments for their identifications are systematically summarized. Thirdly, the advanced electronic nose and photonic nose technologies for volatile organic compounds (VOCs) detection are well introduced. The existed obstacles and future perspectives are deeply thought and discussed. This article could give a good guidance to researchers in this interdisciplinary field, not only understanding the cutting-edge detection technologies for doctors (medicinal background), but also making reference to clarify the choice of aimed VOCs during the sensor research for chemists, materials scientists, electronics engineers, etc.

Are Volatile Organic Compounds Accurate Markers in the Assessment of Colorectal Cancer and Inflammatory Bowel Diseases? A Review

Simple Summary

Early diagnosis is crucial for reducing colorectal cancer-related mortality in both the general population and inflammatory bowel disease. Volatile organic compound (VOC) analysis is a promising alternative to the gold standard procedure, endoscopy, for early detection and surveillance of colorectal diseases. This review aimed to provide a general overview of the most recent evidence in this area on VOC testing in breath, stool, and urine samples.

Abstract

Colorectal cancer (CRC) is one of the leading causes of cancer-related death in the Western world. Early detection decreases incidence and mortality. Screening programs based on fecal occult blood testing help identify patients requiring endoscopic examination, but accuracy is far from optimal. Among the alternative strategies, volatile organic compounds (VOCs) represent novel potentially useful biomarkers of colorectal cancer. They also represent a promising tool for the screening of both intestinal inflammation and related CRC. The review is focused on the diagnostic potential of VOCs in sporadic CRC and in inflammatory bowel diseases (IBD), which increase the risk of CRC, analyzing future clinical applications. Despite limitations related to inadequate strength of evidence, differing analytical platforms identify different VOCs, and this unconventional approach for diagnosing colorectal cancer is promising. Some VOC profiles, besides identifying inflammation, seem disease-specific in inflammatory bowel diseases. Thus, breath, urine, and fecal VOCs provide a new and promising clinical approach to differential diagnosis, evaluation of the inflammatory status, and possibly the assessment of treatment efficacy in IBD. Conversely, specific VOC patterns correlating inflammatory bowel disease and cancer risk are still lacking, and studies focused on this issue are strongly encouraged. No prospective studies have assessed the risk of CRC development by using VOCs in samples collected before the onset of disease, both in the general population and in patients with IBD.

Breathomics: Review of Sample Collection and Analysis, Data Modeling and Clinical Applications

Metabolomics research is rapidly gaining momentum in disease diagnosis, on top of other Omics technologies. Breathomics, as a branch of metabolomics is developing in various frontiers, for early and noninvasive monitoring of disease. This review starts with a brief introduction to metabolomics and breathomics. A number of important technical issues in exhaled breath collection and factors affecting the sampling procedures are presented. We review the recent progress in metabolomics approaches and a summary of their applications on the respiratory and non-respiratory diseases investigated by breath analysis. Recent reports on breathomics studies retrieved from Scopus and Pubmed were reviewed in this work. We conclude that analyzing breath metabolites (both volatile and nonvolatile) is valuable in disease diagnoses, and therefore believe that breathomics will turn into a promising noninvasive discipline in biomarker discovery and early disease detection in personalized medicine. The problem of wide variations in the reported metabolite concentrations from breathomics studies should be tackled by developing more accurate analytical methods and sophisticated numerical analytical alogorithms.

Implementation of quality controls is essential to prevent batch effects in breathomics data and allow for cross-study comparisons

Exhaled breath analysis has become a promising monitoring tool for various ailments by identifying volatile organic compounds (VOCs) as indicative biomarkers excreted in the human body. Throughout the process of sampling, measuring, and data processing, non-biological variations are introduced in the data leading to batch effects. Algorithmic approaches have been developed to cope with within-study batch effects. Batch differences, however, may occur among different studies too, and up-to-date, ways to correct for cross-study batch effects are lacking; ultimately, cross-study comparisons to verify the uniqueness of found VOC profiles for a specific disease may be challenging. This study applies within-study batch-effect-correction approaches to correct for cross-study batch effects; suggestions are made that may help prevent the introduction of cross-study variations. Three batch-effect-correction algorithms were investigated: zero-centering, combat, and the analysis of covariance framework. The breath samples were collected from inflammatory bowel disease ([Formula: see text]), chronic liver disease ([Formula: see text]), and irritable bowel syndrome ([Formula: see text]) patients at different periods, and they were analysed via gas chromatography-mass spectrometry. Multivariate statistics were used to visualise and verify the results. The visualisation of the data before any batch-effect-correction technique was applied showed a clear distinction due to probable batch effects among the datasets of the three cohorts. The visualisation of the three datasets after implementing all three correction techniques showed that the batch effects were still present in the data. Predictions made using partial least squares discriminant analysis and random forest confirmed this observation. The within-study batch-effect-correction approaches fail to correct for cross-study batch effects present in the data. The present study proposes a framework for systematically standardising future breathomics data by using internal standards or quality control samples at regular analysis intervals. Further knowledge regarding the nature of the unsolicited variations among cross-study batches must be obtained to move the field further.