Background
Dysbiosis in the gut microbial community might be involved in the pathophysiology of attention‐deficit/hyperactivity disorder (ADHD). The fungal component of the gut microbiome, namely the ...mycobiota, is a hyperdiverse group of multicellular eukaryotes that can influence host intestinal permeability. This study therefore aimed to investigate the impact of fungal mycobiome dysbiosis and intestinal permeability on ADHD.
Methods
Faecal samples were collected from 35 children with ADHD and from 35 healthy controls. Total DNA was extracted from the faecal samples and the internal transcribed spacer regions were sequenced using high‐throughput next‐generation sequencing (NGS). The fungal taxonomic classification was analysed using bioinformatics tools and the differentially expressed fungal species between the ADHD and healthy control groups were identified. An in vitro permeability assay (Caco‐2 cell layer) was used to evaluate the biological effects of fungal dysbiosis on intestinal epithelial barrier function.
Results
The β‐diversity (the species diversity between two communities), but not α‐diversity (the species diversity within a community), reflected the differences in fungal community composition between ADHD and control groups. At the phylum level, the ADHD group displayed a significantly higher abundance of Ascomycota and a significantly lower abundance of Basidiomycota than the healthy control group. At the genus level, the abundance of Candida (especially Candida albicans) was significantly increased in ADHD patients compared to the healthy controls. In addition, the in vitro cell assay revealed that C. albicans secretions significantly enhanced the permeability of Caco‐2 cells.
Conclusions
The current study is the first to explore altered gut mycobiome dysbiosis using the NGS platform in ADHD. The findings from this study indicated that dysbiosis of the fungal mycobiome and intestinal permeability might be associated with susceptibility to ADHD.
Detection of nodal micrometastasis (tumor size: 0.2–2.0 mm) is challenging for pathologists due to the small size of metastatic foci. Since lymph nodes with micrometastasis are counted as positive ...nodes, detecting micrometastasis is crucial for accurate pathologic staging of colorectal cancer. Previously, deep learning algorithms developed with manually annotated images performed well in identifying micrometastasis of breast cancer in sentinel lymph nodes. However, the process of manual annotation is labor intensive and time consuming. Multiple instance learning was later used to identify metastatic breast cancer without manual annotation, but its performance appears worse in detecting micrometastasis. Here, we developed a deep learning model using whole-slide images of regional lymph nodes of colorectal cancer with only a slide-level label (either a positive or negative slide). The training, validation, and testing sets included 1963, 219, and 1000 slides, respectively. A supercomputer TAIWANIA 2 was used to train a deep learning model to identify metastasis. At slide level, our algorithm performed well in identifying both macrometastasis (tumor size > 2.0 mm) and micrometastasis with an area under the receiver operating characteristics curve (AUC) of 0.9993 and 0.9956, respectively. Since most of our slides had more than one lymph node, we then tested the performance of our algorithm on 538 single-lymph node images randomly cropped from the testing set. At single-lymph node level, our algorithm maintained good performance in identifying macrometastasis and micrometastasis with an AUC of 0.9944 and 0.9476, respectively. Visualization using class activation mapping confirmed that our model identified nodal metastasis based on areas of tumor cells. Our results demonstrate for the first time that micrometastasis could be detected by deep learning on whole-slide images without manual annotation.
Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder, but the underlying pathophysiological mechanisms of ADHD remain unclear. Gut microbiota has been recognized to ...influence brain function and behaviors. Therefore, this study aimed to determine whether imbalanced gut microbiomes identified by a 16S rRNA sequencing approach are involved in the pathophysiology of ADHD. We recruited a total of 30 children with ADHD (mean age: 8.4 years) and a total of 30 healthy controls (mean age: 9.3 years) for this study. The dietary patterns of all participants were assessed with the food frequency questionnaire. The microbiota of fecal samples were investigated using 16S rRNA V3V4 amplicon sequencing, followed by bioinformatics and statistical analyses. We found that the gut microbiota communities in ADHD patients showed a significantly higher Shannon index and Chao index than the control subjects. Furthermore, the linear discriminant analysis effect size (LEfSe) analysis was used to identify differentially enriched bacteria between ADHD patients and healthy controls. The relative abundance of
Bacteroides coprocola
(
B. coprocola
) was decreased, while the relative abundance of
Bacteroides uniformis
(
B. uniformis
),
Bacteroides ovatus
(
B. ovatus
), and
Sutterella stercoricanis
(
S. stercoricanis
) were increased in the ADHD group. Of all participants,
S. stercoricanis
demonstrated a significant association with the intake of dairy, nuts/seeds/legumes, ferritin and magnesium.
B. ovatus
and
S. stercoricanis
were positively correlated to ADHD symptoms. In conclusion, we suggest that the gut microbiome community is associated with dietary patterns, and linked to the susceptibility to ADHD.
Myelodysplastic syndrome (MDS) is a heterogeneous group of clonal myeloid malignancies. Though several recurrent mutations are closely correlated with clinical outcomes, data concerning the ...association between mutation variant allele frequencies (VAF) and prognosis are limited. In this study, we performed comprehensive VAF analyses of relevant myeloid‐malignancy related mutations in 698 MDS patients and correlated the results with their prognosis. Mutation VAF in DNMT3A, TET2, ASXL1, EZH2, SETBP1, BCOR, SFSF2, ZRSR2, and TP53 mutations correlated with outcomes. In multivariable analysis, DNMT3A and ZRSR2 mutations with high VAF and mutant IDH2, CBL, U2AF1, and TP53 were independent poor prognostic factors for overall survival. A substantial portion of patients in each revised International Prognostic Scoring System (IPSS‐R) risk group could be adjusted to different prognostic groups based on the integrated VAF and mutational profiles. Patients with these unfavorable mutations in each IPSS‐R risk subgroup had survivals worse than other patients of the same risk but similar to those in the next higher‐risk subgroup. Furthermore, patients harboring U2AF1 mutation might benefit from hypomethylating agents. This study demonstrated the critical role of VAF of mutations for risk stratification in MDS patients and may be incorporated in novel scoring systems.
DNMT3A mutations are associated with poor prognosis in acute myeloid leukemia (AML), but the stability of this mutation during the clinical course remains unclear. In the present study of 500 ...patients with de novo AML, DNMT3A mutations were identified in 14% of total patients and in 22.9% of AML patients with normal karyotype. DNMT3A mutations were positively associated with older age, higher WBC and platelet counts, intermediate-risk and normal cytogenetics, FLT3 internal tandem duplication, and NPM1, PTPN11, and IDH2 mutations, but were negatively associated with CEBPA mutations. Multivariate analysis demonstrated that the DNMT3A mutation was an independent poor prognostic factor for overall survival and relapse-free survival in total patients and also in normokaryotype group. A scoring system incorporating the DNMT3A mutation and 8 other prognostic factors, including age, WBC count, cytogenetics, and gene mutations, into survival analysis was very useful in stratifying AML patients into different prognostic groups (P < .001). Sequential study of 138 patients during the clinical course showed that DNMT3A mutations were stable during AML evolution. In conclusion, DNMT3A mutations are associated with distinct clinical and biologic features and poor prognosis in de novo AML patients. Furthermore, the DNMT3A mutation may be a potential biomarker for monitoring of minimal residual disease.
The 2022 International Consensus Classification (ICC) recategorized myeloid neoplasms based on recent advances in the understanding of the biology of hematologic malignancies, in which ...myelodysplastic syndrome (MDS) with blasts of 10%–19% is classified as MDS/acute myeloid leukemia (AML), MDS with mutated SF3B1, irrespective of the number of ring sideroblasts, as MDS‐SF3B1, and those with multi‐hit TP53 mutations as MDS with mutated TP53. In the analysis of 716 patients with MDS diagnosed according to the 2016 WHO classification, we found that 75.3% of patients remained in the MDS group based on the ICC, while 24.7% of patients were reclassified to the MDS/AML group after the exclusion of 15 patients who were classified to the AML group. Patients with MDS/AML showed a distinct mutational landscape and had poorer outcomes, compared to those with MDS. In the MDS group, patients with MDS‐SF3B1 had higher frequencies of DNMT3A and TET2 mutations than those with MDS, not otherwise specified, with single lineage dysplasia or multilineage dysplasia. Patients with mutated TP53 were associated with dismal outcomes, irrespective of the blast percentage. In conclusion, this study showed that the ICC facilitates efficient segregation and risk‐stratification of MDS which can help guide the treatment choice of patients with the disease.
Case allocation of MDS patients defined by 2016 WHO classification and 2022 ICC.
Chronic obstructive pulmonary disease (COPD) is a progressive, life-threatening lung disease with increasing prevalence and incidence worldwide. Increasing evidence suggests that lung microbiomes ...might play a physiological role in acute exacerbations of COPD. The objective of this study was to characterize the association of the microbiota and exacerbation risk or airflow limitation in stable COPD patients.
The sputum microbiota from 78 COPD outpatients during periods of clinical stability was investigated using 16S rRNA V3-V4 amplicon sequencing. The microbiome profiles were compared between patients with different risks of exacerbation, i.e., the low risk exacerbator (LRE) or high risk exacerbator (HRE) groups, and with different airflow limitation severity, i.e., mild to moderate (FEV1 ≥ 50; PFT I) or severe to very severe (FEV1 < 50; PFT II).
The bacterial diversity (Chao1 and observed OTUs) was significantly decreased in the HRE group compared to that in the LRE group. The top 3 dominant phyla in sputum were Firmicutes, Actinobacteria, and Proteobacteria, which were similar in the HRE and LRE groups. At the genus level, compared to that in the LRE group (41.24%), the proportion of Streptococcus was slightly decreased in the HRE group (28.68%) (p = 0.007). However, the bacterial diversity and the proportion of dominant bacteria at the phylum and genus levels were similar between the PFT I and PFT II groups. Furthermore, the relative abundances of Gemella morbillorum, Prevotella histicola, and Streptococcus gordonii were decreased in the HRE group compared to those in the LRE group according to linear discriminant analysis effect size (LEfSe). Microbiome network analysis suggested altered bacterial cooperative regulation in different exacerbation phenotypes. The proportions of Proteobacteria and Neisseria were negatively correlated with the FEV1/FVC value. According to functional prediction of sputum bacterial communities through Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis, genes involved in lipopolysaccharide biosynthesis and energy metabolism were enriched in the HRE group.
The present study revealed that the sputum microbiome changed in COPD patients with different risks of exacerbation. Additionally, the bacterial cooperative networks were altered in the HRE patients and may contribute to disease exacerbation. Our results provide evidence that sputum microbiome community dysbiosis is associated with different COPD phenotypes, and we hope that by understanding the lung microbiome, a potentially modifiable clinical factor, further targets for improved COPD therapies during the clinically stable state may be elucidated.
The studies concerning clinical implications of TET2 mutation in patients with primary acute myeloid leukemia (AML) are scarce. We analyzed TET2 mutation in 486 adult patients with primary AML. TET2 ...mutation occurred in 13.2% of our patients and was closely associated with older age, higher white blood cell and blast counts, lower platelet numbers, normal karyotype, intermediate-risk cytogenetics, isolated trisomy 8, NPM1 mutation, and ASXL1 mutation but mutually exclusive with IDH mutation. TET2 mutation is an unfavorable prognostic factor in patients with intermediate-risk cytogenetics, and its negative impact was further enhanced when the mutation was combined with FLT3-ITD, NPM1-wild, or unfavorable genotypes (other than NPM1+/FLT3-ITD− or CEBPA+). A scoring system integrating TET2 mutation with FLT3-ITD, NPM1, and CEBPA mutations could well separate AML patients with intermediate-risk cytogenetics into 4 groups with different prognoses (P < .0001). Sequential analysis revealed that TET2 mutation detected at diagnosis was frequently lost at relapse; rarely, the mutation was acquired at relapse in those without TET2 mutation at diagnosis. In conclusion, TET2 mutation is associated with poor prognosis in AML patients with intermediate-risk cytogenetics, especially when it is combined with other adverse molecular markers. TET2 mutation appeared to be unstable during disease evolution.
Cytomegalovirus (CMV) colitis significantly complicates the course of inflammatory bowel disease (IBD), frequently leading to severe flare-ups and poor outcomes. The role of antiviral therapy in ...hospitalized IBD patients with CMV colitis is currently under debate. This retrospective analysis seeks to clarify the influence of antiviral treatment on these patients.
We retrospectively reviewed IBD patients diagnosed with CMV colitis via immunohistochemistry staining from colonic biopsies at a major tertiary center from January 2000 to May 2021. The study focused on patient demographics, clinical features, risk factors, prognostic indicators, and antiviral treatment outcomes.
Among 118 inpatients, 42 had CMV colitis. Risk factors included hypoalbuminemia and antibiotic use. IBD patients with CMV colitis receiving < 14 days of antiviral therapy had higher complication (72% vs. 43%, p = 0.028) and surgery rates (56% vs. 26%, p = 0.017) compared to those without CMV. Adequate antiviral therapy (≥ 14 days) significantly reduced complications in the CMV group (29% vs. 72%, p = 0.006), especially in Crohn's disease (20% vs. 100%, p = 0.015). Independent predictors of IBD-related complications were CMV colitis (Odds Ratio OR 3.532, 90% Confidence Interval CI 1.012-12.331, p = 0.048), biological treatment failure (OR 4.953, 95% CI 1.91-12.842, p = 0.001), and adequate antiviral therapy (OR 0.108, 95% CI 0.023-0.512, p = 0.005).
CMV colitis and a history of biological treatment failure increase complication risks in IBD patients. Adequate antiviral therapy significantly mitigates these risks, highlighting its importance in managing IBD patients with CMV colitis.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The initial step to interpreting putative biological functions from comparative multi-omics studies usually starts from a differential expressed gene list followed by functional enrichment analysis ...(FEA). However, most FEA packages are designed exclusively for humans and model organisms. Although parasitic protozoan is the most important pathogen in the tropics, no FEA package is available for protozoan functional (ProFun) enrichment analysis. To speed up comparative multi-omics research on parasitic protozoans, we constructed ProFun, a web-based, user-friendly platform for the research community.
ProFun utilizes the Docker container, ShinyProxy, and R Shiny to construct a scalable web service with load-balancing infrastructure. We have integrated a series of visual analytic functions, in-house scripts, and custom-made annotation packages to create three analytical modules for 40 protozoan species: (1) Gene Overlaps; (2) Over-representation Analysis (ORA); (3) Gene Set Enrichment Analysis (GSEA).
We have established ProFun, a web server for functional enrichment analysis of differentially expressed genes. FEA becomes as simple as pasting a list of gene IDs into the textbox of our website. Users can customize enrichment parameters and results with just one click. The intuitive web interface and publication-ready charts enable users to reveal meaningful biological events and pinpoint potential targets for further studies.
ProFun is the first web application that enables gene functional enrichment analysis of parasitic protozoans. In addition to supporting FEA analysis, ProFun also allows the comparison of FEA results across complicated experimental designs. ProFun is freely available at http://dalek.cgu.edu.tw:8080/app/profun.
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