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Record W4386307280 · doi:10.3389/fped.2023.1274735

Editorial: Hirschsprung disease: genetic susceptibility, disease mechanisms and innovative management in the multi-omics era

2023· editorial· en· W4386307280 on OpenAlexaff
Consolato Sergi, Josef Häger

Bibliographic record

VenueFrontiers in Pediatrics · 2023
Typeeditorial
Languageen
FieldMedicine
TopicCongenital gastrointestinal and neural anomalies
Canadian institutionsUniversity of AlbertaChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsDiseaseMedicineOmicsDisease managementHirschsprung's diseaseBioinformaticsIntensive care medicinePathologyBiologyParkinson's disease

Abstract

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Hirschsprung disease (HSCR) remains a puzzling disease and a story of the continuous exploration of the etiology and a non-surgical cure (1). HSCR is a heterogeneous disease with an incidence of 1.5-2.8 per 10,000 births. It is characterized by varying lengths of lack of ganglion cells and hypertrophy of nerve fibers, a male preponderance (M:F-5:1), a variable familial incidence, and occasional syndromic involvement (2,3). In the neonatal period, about 80% of infants (~10% of whom are preterm) present with a delayed passage of meconium (beyond 24 hours), an increasingly distended abdomen, and intermittent vomiting. In individual cases, around 12% of these children may already have an impaired general condition caused by preexisting or developing enterocolitis. In about 10% of children with short-term HSCR, symptoms only appear later, usually during the switch from breastfeeding to pap food, mainly since the soft breast milk stool can be transported through the non-innervated sigmoid/rectal segment without any problems. These children are characterized by an intermittent refusal to eat and rapidly increasing constipation or encopresis. After clinical, radiological and manometric investigations, the current standardized method to diagnose HSCR is a rectal biopsy above the dentate line with the help of a suction device with the subsequent histologic examination (4) (Figure 1).HSCR is a disease affecting patients and families, and the current cure is exclusively surgical. The promise of the Omic-Era is encouraging because the goal is to identify niches where researchers and physicians can meet and improve the outcome of patients affected by this terrible disease (2). The era of high-throughput technologies has the impetus to accelerate its scale dramatically in the 21 st century. Genomics, epigenomics, transcriptomics, proteomics, metabolomics, glycomics, and lipidomics offer an outstanding opportunity for holistic investigation and contextual understanding of the pathogenesis of gastrointestinal disease for precise diagnosis and tailored treatment. This Research Topic has stimulated some researchers to contribute our knowledge of this disease and contribute to this collection.). ARM and HSCR are rarely reported together. The authors report an overall incidence of 2.4-3.4% of cases. The paper is exciting and very precise, with spectacular images. Everything is explained in detail, but importantly, in the case of anal atresia, the simultaneous occurrence of HSCR should be considered.The REarranged during Transfection (RET) is probably one of the most significant genes discovered by 24 genes associated with HSCR (Iskandar et al.). RET's somatic mosaicisms have been identified in HSCR but are poorly recognized. The authors in this special issue underpinned the frequency of rs2435357somatic mutation of RET in HSCR patients. Iskandar et al. suggest that somatic mosaicism in HSCR patients is not uncommon, supporting the complexity of the pathogenesis of this gastrointestinal disorder (Iskandar et al.). They confirm that the RET rs2435357 is a paramount genetic risk factor for HSCR patients. With the help of molecular genetics, it is even possible to detect specific changes in the patient's genetic information. The authors rightly speak of a mosaic status. In this context, RET rs2435357 is of particular importance in HSCR patients. It would be interesting to identify the burden of each mutation in causing HSCR in the future.Wang et al. used the robust linear model (RLM) statistical method. Robust regression uses an iterative approach to assign a weight to each data point. The RLM algorithm uses the leastsquares approach to identify the curve that outbursts the data bulk. The final event is to minimize the effects of outliers. These authors used RLM for screening plasma human autoimmune antigen microarrays. They quantitatively assessed enzyme-linked immunosorbent assay (ELISA) values with single-stranded DNA (ssDNA) antibody levels. They found that ssDNA antibodies in HSCR plasma were considerably higher than those in healthy and disease controls. Further, ssDNA antibodies differentiated HSCR from non-HSCR patients, accomplishing an area under the curve (AUC) of 0.917, harboring a sensitivity of 96.99% and a specificity of 74.63%. The considerations of this work are interesting, especially since they meant an extension of diagnostics. The occurrence of the ssDNA antibody can be promising, especially in premature babies.We are still searching the etiology of HSCR, and the findings of Ji et al. may help us understand one of the life-threatening conditions associated with HSCR. Neuroimmune instruction intercedes the incidence and progress of enteritis. Single-cell RNA sequencing has been critical to decrypt several intracellular processes and signaling mechanisms in the last few years. Both human and mouse gut nervous system (ENS) components demonstrate that healthy gut neuronal cells prompt mediators and cell surface molecules, which can interconnect with innate and adaptive immunologic pathways. The enhancement of the neuromodulatory effect may prevent this entity from occurring. Vasoactive intestinal peptide, substance P, and neuropeptide Y carry a cationic charge that can break the bacterial membranes and kill the microorganisms. The authors describe the characteristics of the interaction between intestinal nerve cells and immune cells. We do not understand in detail what influence the cells in the hypoganglionic section of the megacolon in promoting the inflammatory process, nor the impact of the ganglion cells of the euganglionic megacolon. Understanding the interaction between ganglion cells and immune cells in the case of postoperative enterocolitis seems even more difficult. Is this caused by a disturbance in the peristalsis behind it, although the colon should be functioning after the intervention? Does residual stenosis play a role? Is sphincter achalasia a possible cause? Thus, this topic warrants further exploration.A few centuries following the initial discovery of congenital megacolon in 1691 by Frederick Ruysch, a Dutch Anatomist, and its detailed description in 1886 by Harald Hirschsprung, a Danish pediatrician, HSCR is still very challenging. It will need a comprehensive platform of tools and minds to understand in detail the etiopathogenesis, broaden the diagnostic tools, and set up a non-surgical treatment. Scientists and physicians are called to apply their efforts in tackling this Sisyphean task.Microphotograph of a rectal suction biopsy showing no ganglion cells, but exclusively nerve fibers (Hematoxylin and Eosin staining, X100, scale bar: 50 micrometers).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.273
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.258
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEditorial

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2023
Admission routes1
Has abstractyes

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