To study the effect of host genetics on gut microbiome composition, the MiBioGen consortium curated and analyzed whole-genome genotypes and 16S fecal microbiome data from 18,473 individuals (25 cohorts). Microbial composition showed high variability across cohorts: we detected only 9 out of 410 genera in more than 95% of the samples. A genome-wide association study (GWAS) of host genetic variation in relation to microbial taxa identified 30 loci affecting microbome taxa at a genome-wide significant (P<5×10-8) threshold. Just one locus, the lactase (LCT) gene region, reached study-wide significance (GWAS signal P=8.6×10−21); it showed an age-dependent association with Bifidobacterium abundance. Other associations were suggestive (1.94×10−10<P<5×10−8) but enriched for taxa showing high heritability and for genes expressed in the intestine and brain. A phenome-wide association study and Mendelian randomization analyses identified enrichment of microbiome trait loci SNPs in the metabolic, nutrition and environment domains and indicated food preferences and diseases as mediators of genetic effects.

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 (n=213), chronic liver disease (n=189), and irritable bowel syndrome (n=261) 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.

With great interest, we have read the article by Backes et al ,1 on the pre-resection accuracy of the real-time optical diagnosis of T1 colorectal cancer (T1CRC) in large non-pedunculated colorectal polyps. In this multicentre, prospective study, the authors developed and validated the OPTICAL model, in which a sensitivity of 78.7% (95% CI: 64.3 to 89.3) for optical diagnosis of T1CRC was obtained. With the implementation of the Dutch bowel cancer screening programme (BCSP) in 2014, a shift has occurred towards the more frequent diagnoses of early AJCC (American Joint Committee on Cancer) stage I cancers.2 Estimating the risk of a T1CRC is crucial to determine the optimal treatment strategy, and to select cases for more elaborative and expensive endoscopic en bloc resection techniques such as endoscopic submucosal dissection, transanal minimally invasive surgery or endoscopic full-thickness resection. Current studies mainly report on the outcomes of advanced imaging by expert centres with dedicated endoscopists,3 4 whereas …

We thank dr Yuanjun Dong for his interest in our publication.1 Dr Dong points out that previous and current stressful life events mod‐ ulate gastrointestinal (GI) symptom severity and quality of life (QoL) in patients with irritable bowel syndrome (IBS),2 which is indeed based on recent findings.3 In addition, we would like to note that abdominal pain is the predominant symptom in IBS, as per Rome IV definition. The primary treatment outcome for IBS in clinical tri‐ als, in accordance with FDA and EMA requirements, is reduction in daily abdominal pain.4 Whether a successful treatment, based on these criteria, improves patients’ life satisfaction and QoL remains an item of debate. In the current study, we performed an extensive prospective evaluation of the natural course of IBS which included demographics, gastrointestinal symptoms, symptoms of anxiety and depression, GI‐specific anxiety, satisfaction with life, and QoL. With regard to QoL, we showed among others that general anxiety and depression levels at follow‐up were independently associated with mental quality of life scores at the same time point. Furthermore, no associations were found between GI symptom severity, including abdominal pain, and the change in QoL scores over time.1 With regard to a possible interaction between GI symptoms and stress, in Table 1 we provide data on specific questions and answers from the database of Maastricht IBS cohort regarding the patients’ perspective on this matter. No statistically significant differences were found between Rome‐positive and Rome‐negative IBS patients at follow‐up. However, the current understanding on the relationship between abdominal pain and stress, whether current or related to life events, may be limited by the methods used to assess these factors. Traditionally, data from retrospective reports have been used to de‐ scribe this relationship, but it is known that these questionnaires are limited by recall and ecological bias.4 We therefore believe that the best available method to study the relationship between GI symp‐ toms, comorbid psychological complaints, and daily life stress is re‐ peated momentary symptom assessment.5 Such methodology has been used recently to assess the temporal relationship between ab‐ dominal pain and (preceding) daily life stress.6 We have developed and are currently validating specific questionnaires based on experience sampling method (ESM) which may provide additional leads in this matter.7 In a recently completed study, we demonstrate that real‐time stress scores are positively associated with concurrent abdominal pain scores in IBS, but not in healthy subjects, whereas abdominal pain could not be predicted by preceding stress levels, and vice versa, suggesting an in‐the‐moment rather than a longitudinal association.8 Taken together, we postulate that reduction in abdominal pain is not necessarily accompanied by long‐term improvement in quality of life in patients with IBS. This may indicate that the primary treat‐ ment focus in IBS should shift from solely abdominal pain reduction and improvement of bowel habits, toward a holistic approach, which includes quality of life, comorbid psychological symptoms, and im‐ provement of coping strategies with regard to GI symptoms as well as daily life stress. However, the evidence to support a change in the approach of IBS management is still inconclusive, and further research is needed.

The human gut microbiome is influenced by numerous factors including commonly used drugs, but it has also been shown that the gut microbiome by itself influences drug responses and efficacy. We studied the relations between commonly used drugs and microbial changes considering factors like polypharmacy and multi-morbidity. We performed metagenomics sequencing of 1883 faecal samples from three cohorts: 1) a population-based cohort, 2) patients with inflammatory bowel diseases and 3) patients with irritable bowel syndrome. Differences between drug users and non-users were analysed per cohort, followed by a meta-analysis. 17 of 41 drugs were associated with changes in microbial features. For example, metformin users showed enrichment of Escherichia-coli -derived metabolic pathways and methanogenic pathways were increased in oral steroid users in patients with IBD. Due the importance of the gut microbiome in health and the widespread use of drugs, we here provide evidence for extensive changes in taxonomy, metabolic activity and resistome in relation to commonly used drugs. This research paves the way to further mechanistic studies for drug response and side effects and has implications on future microbiome studies, underlining the need for correcting for multiple drug use in both general population and in GI disease cohorts.

Irritable bowel syndrome (IBS) is a brain‐gut disorder, of which the natural course varies between patients and is difficult to predict. This study aimed to evaluate symptom evolution over a 5‐year follow‐up period and to identify baseline predictors for symptom severity and quality of life (QoL) at follow‐up.

Differences in gut microbiota composition and function were observed between patients with inflammatory bowel disease or irritable bowel syndrome. Distinguishing two similar gut disorders Inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS) are two of the most common diseases of the gastrointestinal tract. In new work, Vich Vila and colleagues have characterized the gut microbiota composition of both disorders using shotgun metagenomic sequencing of stool samples from 1792 individuals. Analyses involving bacterial taxonomy, metabolic functions, antibiotic resistance genes, virulence factors, and bacterial growth rates showed key differences between these two gut disorders. On the basis of gut microbiota composition differences, patients with IBD could be distinguished from those with IBS. Changes in the gut microbiota have been associated with two of the most common gastrointestinal diseases, inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS). Here, we performed a case-control analysis using shotgun metagenomic sequencing of stool samples from 1792 individuals with IBD and IBS compared with control individuals in the general population. Despite substantial overlap between the gut microbiome of patients with IBD and IBS compared with control individuals, we were able to use gut microbiota composition differences to distinguish patients with IBD from those with IBS. By combining species-level profiles and strain-level profiles with bacterial growth rates, metabolic functions, antibiotic resistance, and virulence factor analyses, we identified key bacterial species that may be involved in two common gastrointestinal diseases.

Introduction: The aim of this study was to determine the serum levels of malondialdehyde (MDA) in patients with invasive breast cancer in relation to its serum levels in patients with benign breast disease, and to investigate correlation between MDA serum levels with pathohistological prognostic factors (tumor size, lymph node involvement, and histologic grade [HG]), estrogen receptor (ER) status, and with breast cancer patient’s age and menopausal status. Methods: A total of 43 with well-documented invasive breast cancer were included in this study: 27 with positive axillary’s lymph nodes, and 16 with negative axillary’s lymph nodes, and 39 patients with findings of benign breast diseases. MDA determination in serum of breast cancer and benign breast disease patients was performed by the fluorimetric method, immunohistochemical staining was performed for ER, and routine pathohistological examination was conducted for pathohistological factors. Results: MDA serum levels in breast cancer patients were significantly higher than MDA serum levels in benign breast disease patients (p = 0.042). No statistically significant difference between MDA serum levels in breast cancer patients with and without lymph node metastases was found (p = 0.238). No statistically significant correlations between MDA serum levels and tumor size (p = 0.256), HG (p = 0.124), or number of positive lymph nodes (0.113) were found. A statistically significant correlation between serum MDA levels and ages of breast cancer patients with lymph node metastases was found (p = 0.006). Conclusion: Obtained results support the importance of MDA in the carcinogenesis of breast cancer. According to our findings, serum level of MDA could not be a useful prognostic factor in breast cancer.