scholarly journals Quantitative proteomics reveal neuron projection development genes ARF4, KIF5B and RAB8A associated with Hirschsprung disease

2020 ◽  
pp. mcp.RA120.002325
Author(s):  
Qin Zhang ◽  
Lihua Wu ◽  
Baoling Bai ◽  
Dan Li ◽  
Ping Xiao ◽  
...  
Keyword(s):  
Quantitative Proteomics ◽  
Large Scale ◽  
Bioinformatics Analysis ◽  
Hirschsprung Disease ◽  
Human Colon ◽  
Incomplete Penetrance ◽  
Short Segment ◽  
Pathogenic Variants ◽  
Enteric Ganglia ◽  
Parallel Reaction Monitoring

Hirschsprung disease (HSCR) is a heterogeneous group of neurocristopathy characterized by the absence of the enteric ganglia along a variable length of the intestine. Genetic defects play a major role in the pathogenesis of HSCR while family studies of pathogenic variants in all the known genes (loci) only demonstrate incomplete penetrance and variable expressivity for unknown reasons. Here, we applied large-scale, quantitative proteomics of human colon tissues from 21 patients using iTRAQ method followed by bioinformatics analysis. Selected findings were confirmed by parallel reaction monitoring (PRM) verification. At last the interesting differentially expressed proteins were confirmed by western blot. A total of 5341 proteins in human colon tissues were identified. Among them, 664 proteins with >1.2-fold difference were identified in 6 groups: groups A1 and A2 pooled protein from the ganglionic and aganglionic colon of male, long-segment HSCR patients (L-HSCR, n=7); groups B1 and B2 pooled protein from the ganglionic and aganglionic colon of male, short-segment HSCR patients (S-HSCR, n=7); and groups C1 and C2 pooled protein from the ganglionic and aganglionic colon of female, S-HSCR patients (n=7). Based on these analyses, 49 proteins from 5 pathways were selected for PRM verification, including ribosome, endocytosis, spliceosome, oxidative phosphorylation and cell adhesion. The downregulation of three neuron projection development genes ARF4, KIF5B and RAB8A in the aganglionic part of the colon were verified in 15 paired colon samples using WB. The findings of this study will shed new light on the pathogenesis of HSCR and facilitate the development of therapeutic targets.

scholarly journals Sequence characterization of RET in 117 Chinese Hirschsprung disease families identifies a large burden of de novo and parental mosaic mutations

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Qian Jiang ◽  
Yang Wang ◽  
Qi Li ◽  
Zhen Zhang ◽  
Ping Xiao ◽  
...  
Keyword(s):  
De Novo ◽  
Hirschsprung Disease ◽  
Causative Gene ◽  
High Coverage ◽  
Chinese Families ◽  
Sequence Characterization ◽  
Pathogenic Variants ◽  
Enteric Ganglia ◽  
Digital Polymerase Chain Reaction ◽  
Coding Variants

Abstract Background Hirschsprung disease (HSCR) is an inherited congenital disorder characterized by the absence of enteric ganglia in the distal part of the gut. RET is the major causative gene and contains > 80% of all known disease-causing mutations. Results To determine the incidence of RET pathogenic variants, be they Mendelian inherited, mosaic in parents or true de novo variants (DNVs) in 117 Chinese families, we used high-coverage NGS and droplet digital polymerase chain reaction (ddPCR) to identify 15 (12.8%) unique RET coding variants (7 are novel); one was inherited from a heterozygous unaffected mother, 11 were DNVs (73.3%), and 3 full heterozygotes were inherited from parental mosaicism (2 paternal, 1 maternal): two clinically unaffected parents were identified by NGS and confirmed by ddPCR, with mutant allele frequency (13–27%) that was the highest in hair, lowest in urine and similar in blood and saliva. An extremely low-level paternal mosaicism (0.03%) was detected by ddPCR in blood. Six positive-controls were examined to compare the mosaicism detection limit and sensitivity of NGS, amplicon-based deep sequencing and ddPCR. Conclusion Our findings expand the clinical and molecular spectrum of RET variants in HSCR and reveal a high frequency of RET DNVs in the Chinese population.

scholarly journals Functional outcomes of patients with short-segment Hirschsprung disease after transanal endorectal pull-through

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Gunadi ◽  
Gabriele Ivana ◽  
Desyifa Annisa Mursalin ◽  
Ririd Tri Pitaka ◽  
Muhammad Wildan Zain ◽  
...  
Keyword(s):  
Functional Outcomes ◽  
Hirschsprung Disease ◽  
Treatment Method ◽  
Strongly Correlated ◽  
Short Segment ◽  
Multicenter Studies ◽  
Operative Complications ◽  
Pull Through ◽  
Larger Sample ◽  
Post Operative Complications

Abstract Background Transanal endorectal pull-through (TEPT) is considered the most preferable treatment method for Hirschsprung disease (HSCR) since it is less invasive and has fewer morbidities than transabdominal pull-through. Here, functional outcomes in short-segment HSCR patients after TEPT were assessed and associated with the prognostic factors. Methods Krickenbeck classification was used to assess the functional outcomes in patients with HSCR after TEPT surgery at our institution from 2012 to 2020. Results Fifty patients were involved in this study. Voluntary bowel movement (VBM) was achieved in 82% of subjects. Nine (18%) subjects had soiling grade 1, while two (4%) and two (4%) patients suffered constipation that was manageable with diet and laxative agents, respectively. Patients who underwent TEPT at ≥ 4 years old tended to have soiling more than patients who underwent TEPT at < 4 years old (OR = 16.47 [95% CI 0.9–301.61]; p = 0.06), whereas patients with post-operative complications had 10.5-fold higher risk for constipation than patients without post-operative complications (p = 0.037; 95% CI 1.15–95.92). Multivariate analysis showed male sex was significantly associated with VBM (OR = 9.25 [95% CI 1.34–63.77]; p = 0.024), while post-operative complications were strongly correlated with constipation (OR = 10 [95% CI 1.09–91.44]; p = 0.04). Conclusions The functional outcomes of HSCR patients after TEPT in our institution are considered relatively good. Moreover, the VBM, soiling, and constipation risk after TEPT might be affected by sex, age at TEPT performed, and post-operative complications, respectively, while the age at TEPT performed might not be associated with functional outcomes. Further multicenter studies with a larger sample size are necessary to clarify and confirm our findings.

Frequency and characterization of mutations in genes in a large cohort of patients referred to MODY registry

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Emily Breidbart ◽  
Liyong Deng ◽  
Patricia Lanzano ◽  
Xiao Fan ◽  
Jiancheng Guo ◽  
...  
Keyword(s):  
Genetic Testing ◽  
Exome Sequencing ◽  
Large Scale ◽  
Age Of Onset ◽  
Family Members ◽  
Ethnically Diverse ◽  
Monogenic Diabetes ◽  
Diabetes Diagnosis ◽  
Pathogenic Variants ◽  
Atypical Diabetes

Abstract Objectives There have been few large-scale studies utilizing exome sequencing for genetically undiagnosed maturity onset diabetes of the young (MODY), a monogenic form of diabetes that is under-recognized. We describe a cohort of 160 individuals with suspected monogenic diabetes who were genetically assessed for mutations in genes known to cause MODY. Methods We used a tiered testing approach focusing initially on GCK and HNF1A and then expanding to exome sequencing for those individuals without identified mutations in GCK or HNF1A. The average age of onset of hyperglycemia or diabetes diagnosis was 19 years (median 14 years) with an average HbA1C of 7.1%. Results Sixty (37.5%) probands had heterozygous likely pathogenic/pathogenic variants in one of the MODY genes, 90% of which were in GCK or HNF1A. Less frequently, mutations were identified in PDX1, HNF4A, HNF1B, and KCNJ11. For those probands with available family members, 100% of the variants segregated with diabetes in the family. Cascade genetic testing in families identified 75 additional family members with a familial MODY mutation. Conclusions Our study is one of the largest and most ethnically diverse studies using exome sequencing to assess MODY genes. Tiered testing is an effective strategy to genetically diagnose atypical diabetes, and familial cascade genetic testing identified on average one additional family member with monogenic diabetes for each mutation identified in a proband.

scholarly journals Clinical characteristics of Polish patients with molecularly confirmed Mowat-Wilson syndrome

2021 ◽  
Author(s):  
Aleksandra Jakubiak ◽  
Krzysztof Szczałuba ◽  
Magdalena Badura-Stronka ◽  
Anna Kutkowska-Kaźmierczak ◽  
Anna Jakubiuk-Tomaszuk ◽  
...  
Keyword(s):  
Intellectual Disability ◽  
Congenital Anomalies ◽  
Chromosomal Region ◽  
Neurodevelopmental Disorder ◽  
Hirschsprung Disease ◽  
Psychomotor Retardation ◽  
Facial Features ◽  
Dysmorphic Features ◽  
Pathogenic Variants ◽  
Intragenic Deletions

AbstractMowat-Wilson syndrome is a rare neurodevelopmental disorder caused by pathogenic variants in the ZEB2 gene, intragenic deletions of the ZEB2 gene, and microdeletions in the critical chromosomal region 2q22-23, where the ZEB2 gene is located. Mowat-Wilson syndrome is characterized by typical facial features that change with the age, severe developmental delay with intellectual disability, and multiple congenital abnormalities. The authors describe the clinical and genetic aspects of 28th patients with Mowat-Wilson syndrome diagnosed in Poland. Characteristic dysmorphic features, psychomotor retardation, intellectual disability, and congenital anomalies were present in all cases. The incidence of most common congenital anomalies (heart defect, Hirschsprung disease, brain defects) was similar to presented in literature. Epilepsy was less common compared to previously reported cases. Although the spectrum of disorders in patients with Mowat-Wilson syndrome is wide, knowledge of characteristic dysmorphic features awareness of accompanying abnormalities, especially intellectual disability, improves detection of the syndrome.

Comparative Analysis of Modified Laparoscopic Swenson and Laparoscopic Soave Procedure for Short-Segment Hirschsprung Disease in Children

2014 ◽  
Vol 25 (05) ◽  
pp. 430-434
Author(s):  
Yaohao Wu ◽  
LeXiang Zeng ◽  
Jie Zhang ◽  
Jiajia Zhou ◽  
Ronglin Qiu ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Hirschsprung Disease ◽  
Short Segment

scholarly journals SVFX: a machine-learning framework to quantify the pathogenicity of structural variants

2019 ◽  
Author(s):  
Sushant Kumar ◽  
Arif Harmanci ◽  
Jagath Vytheeswaran ◽  
Mark B. Gerstein
Keyword(s):  
Machine Learning ◽  
Large Scale ◽  
Three Dimensional ◽  
Point Mutations ◽  
Dimensional Structure ◽  
Rapid Decline ◽  
Ras Signaling ◽  
Cancer Genes ◽  
Structural Variations ◽  
Pathogenic Variants

AbstractA rapid decline in sequencing cost has made large-scale genome sequencing studies feasible. One of the fundamental goals of these studies is to catalog all pathogenic variants. Numerous methods and tools have been developed to interpret point mutations and small insertions and deletions. However, there is a lack of approaches for identifying pathogenic genomic structural variations (SVs). That said, SVs are known to play a crucial role in many diseases by altering the sequence and three-dimensional structure of the genome. Previous studies have suggested a complex interplay of genomic and epigenomic features in the emergence and distribution of SVs. However, the exact mechanism of pathogenesis for SVs in different diseases is not straightforward to decipher. Thus, we built an agnostic machine-learning-based workflow, called SVFX, to assign a “pathogenicity score” to somatic and germline SVs in various diseases. In particular, we generated somatic and germline training models, which included genomic, epigenomic, and conservation-based features for SV call sets in diseased and healthy individuals. We then applied SVFX to SVs in six different cancer cohorts and a cardiovascular disease (CVD) cohort. Overall, SVFX achieved high accuracy in identifying pathogenic SVs. Moreover, we found that predicted pathogenic SVs in cancer cohorts were enriched among known cancer genes and many cancer-related pathways (including Wnt signaling, Ras signaling, DNA repair, and ubiquitin-mediated proteolysis). Finally, we note that SVFX is flexible and can be easily extended to identify pathogenic SVs in additional disease cohorts.

scholarly journals ComplexBrowser: a tool for identification and quantification of protein complexes in large scale proteomics datasets

2019 ◽  
Author(s):  
Wojciech Michalak ◽  
Vasileios Tsiamis ◽  
Veit Schwämmle ◽  
Adelina Rogowska-Wrzesińska
Keyword(s):  
T Cell Activation ◽  
Protein Complex ◽  
Quantitative Proteomics ◽  
Large Scale ◽  
Protein Complexes ◽  
Quantitative Measure ◽  
Exploratory Analysis ◽  
List Type ◽  
Link Type ◽  
Complex Components

AbstractWe have developed ComplexBrowser, an open source, online platform for supervised analysis of quantitative proteomics data that focuses on protein complexes. The software uses information from CORUM and Complex Portal databases to identify protein complex components. Based on the expression changes of individual complex subunits across the proteomics experiment it calculates Complex Fold Change (CFC) factor that characterises the overall protein complex expression trend and the level of subunit co-regulation. Thus up- and down-regulated complexes can be identified. It provides interactive visualisation of protein complexes composition and expression for exploratory analysis. It also incorporates a quality control step that includes normalisation and statistical analysis based on Limma test. ComplexBrowser performance was tested on two previously published proteomics studies identifying changes in protein expression in human adenocarcinoma tissue and during activation of mouse T-cells. The analysis revealed 1519 and 332 protein complexes, of which 233 and 41 were found co-ordinately regulated in the respective studies. The adopted approach provided evidence for a shift to glucose-based metabolism and high proliferation in adenocarcinoma tissues and identification of chromatin remodelling complexes involved in mouse T-cell activation. The results correlate with the original interpretation of the experiments and also provide novel biological details about protein complexes affected. ComplexBrowser is, to our knowledge, the first tool to automate quantitative protein complex analysis for high-throughput studies, providing insights into protein complex regulation within minutes of analysis.A fully functional demo version of ComplexBrowser v1.0 is available online via http://computproteomics.bmb.sdu.dk/Apps/ComplexBrowser/The source code can be downloaded from: https://bitbucket.org/michalakw/complexbrowserHighlightsAutomated analysis of protein complexes in proteomics experimentsQuantitative measure of the coordinated changes in protein complex componentsInteractive visualisations for exploratory analysis of proteomics resultsIn briefComplexBrowser is capable of identifying protein complexes in datasets obtained from large scale quantitative proteomics experiments. It provides, in the form of the CFC factor, a quantitative measure of the coordinated changes in complex components. This facilitates assessing the overall trends in the processes governed by the identified protein complexes providing a new and complementary way of interpreting proteomics experiments.

scholarly journals Association between ALS and retroviruses: evidence from bioinformatics analysis

2019 ◽  
Vol 20 (S24) ◽  
Author(s):  
Jon P. Klein ◽  
Zhifu Sun ◽  
Nathan P. Staff
Keyword(s):  
Protein Interaction ◽  
Drug Targets ◽  
Large Scale ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Pathway Enrichment Analysis ◽  
Protein Database ◽  
Core Cluster

Abstract Background Emerging evidence suggests retroviruses play a role in the pathophysiology of amyotrophic lateral sclerosis (ALS). Specifically, activation of ancient viral genes embedded in the human genome is theorized to lead to motor neuron degeneration. We explore whether connections exist between ALS and retroviruses through protein interaction networks (PIN) and pathway analysis, and consider the potential roles in drug target discovery. Protein database and pathway/network analytical software including Ingenuity Pathway BioProfiler, STRING, and CytoScape were utilized to identify overlapping protein interaction networks and extract core cluster (s) of retroviruses and ALS. Results Topological and statistical analysis of the ALS-PIN and retrovirus-PIN identified a shared, essential protein network and a core cluster with significant connections with both networks. The identified core cluster has three interleukin molecules IL10, Il-6 and IL-1B, a central apoptosis regulator TP53, and several major transcription regulators including MAPK1, ANXA5, SQSTM1, SREBF2, and FADD. Pathway enrichment analysis showed that this core cluster is associated with the glucocorticoid receptor singling and neuroinflammation signaling pathways. For confirmation purposes, we applied the same methodology to the West Nile and Polio virus, which demonstrated trivial connectivity with ALS, supporting the unique connection between ALS and retroviruses. Conclusions Bioinformatics analysis provides evidence to support pathological links between ALS and retroviral activation. The neuroinflammation and apoptotic regulation pathways are specifically implicated. The continuation and further analysis of large scale genome studies may prove useful in exploring genes important in retroviral activation and ALS, which may help discover new drug targets.

scholarly journals Spica Prunellae Extract Enhances Fluorouracil Sensitivity of 5-Fluorouracil-Resistant Human Colon Carcinoma HCT-8/5-FU Cells via TOP2α and miR-494

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yi Fang ◽  
Chi Yang ◽  
Ling Zhang ◽  
Lihui Wei ◽  
Jiumao Lin ◽  
...  
Keyword(s):  
Bioinformatics Analysis ◽  
Ethanol Extract ◽  
Human Colon ◽  
Protein Interaction Networks ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Beneficial Effects ◽  
Human Colon Carcinoma ◽  
Public Dataset ◽  
Protein Protein Interaction Networks

The use of 5-fluorouracil (5-FU) has been proven benefits, but it also has adverse events in colorectal cancer (CRC) chemotherapy. In this study, we explored the mechanism of 5-FU resistance by bioinformatics analysis of the NCBI public dataset series GSE81005. Fifteen hub genes were screened out of 582 different expressed genes. Modules of the hub genes in protein-protein interaction networks gathered to TOP2α showed a decrease in HCT-8 cells but an increase in 5-FU-resistant HCT-8/5-FU cells with 5-FU exposure. Downregulation of TOP2α with siRNA or miR-494 transfection resulted in an increase of cytotoxicity and decrease of cell colonies to 5-FU for HCT-8/5-FU cells. Moreover, we found that an ethanol extract of Spica Prunellae (EESP), which is a traditional Chinese medicine with clinically beneficial effects in various cancers, was able to enhance the sensitivity of 5-FU in HCT-8/5-FU cells and partly reverse the 5-FU resistance effect. It significantly helped suppress cell growth and induced cell apoptosis in HCT-8/5-FU cells with the expression of TOP2α being significantly suppressed, which increased by 5-FU. Consistently, miR-494, which reportedly regulates TOP2α, exhibited reverse trends in EESP/5-FU combination treatment. These results suggested that Spica Prunellae may be beneficial in the treatment of 5-FU-resistant CRC patients.

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