Evidence map›Paper›PMID 36713418›Full record

ArticleFrontiers in immunology2022

Identifying and validating molecular subtypes of biliary atresia using multiple high-throughput data integration analysis.

Dingding Wang, Shen Yang, Yong Zhao, Yanan Zhang, Kaiyun Hua, Yichao Gu, Shuangshuang Li, Junmin Liao, Ting Yang, Jiawei Zhao and 1 more

Abstract read
In one paragraph

Article in Frontiers in immunology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Biliary atresia.Nature reviews. Disease primers · 2024
    Review
  5. In Utero Extrahepatic Bile Duct Damage and Repair: Implications for Biliary Atresia.Pediatric and developmental pathology : the official journal of the Society for Pediatric Pathology and the Paediatric Pathology Society
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Dingding WangDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Shen YangDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Yong ZhaoDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Yanan ZhangDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Kaiyun HuaDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Yichao GuDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Shuangshuang LiDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Junmin LiaoDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Ting YangDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Jiawei ZhaoDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.
Jinshi HuangDepartment of Neonatal Surgery, Beijing Children's Hospital, Capital Medical University, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Biliary atresia (BA) is the most common form of severe neonatal obstructive jaundice. The etiology and pathogenesis of BA are multifactorial, and different factors may interact to produce heterogeneous pathological features and clinical outcomes. Despite different pathological features, all patients received the same treatment strategy. This study performed integrative clustering analysis based on multiple high-throughput datasets to identify the molecular subtypes of BA and provide a new treatment strategy for personalized treatment of the different subtypes of BA. Methods: The RNA sequence dataset GSE122340 in the Gene Expression Omnibus (GEO) database was downloaded; 31 BA and 20 control normal liver tissues were collected at our center for transcriptome sequencing, and clinical and follow-up data of BA patients were available. Molecular subtypes were identified using integrated unsupervised cluster analysis involving gene expression, biliary fibrosis, and immune enrichment scores based on the transcriptome dataset, and the results were validated using independent datasets. Results: Based on the results of the integrated unsupervised clustering analysis, four molecular subtypes were identified: autoimmune, inflammatory, virus infection-related, and oxidative stress. The autoimmune subtype with a moderate prognosis was dominated by autoimmune responses and morphogenesis, such as the Fc-gamma receptor and Wnt signaling pathway. The biological process of the inflammatory subtype was mainly the inflammatory response, with the best prognosis, youngest age at surgery, and lowest liver stiffness. The virus infection-related subtype had the worst prognosis and was enriched for a variety of biological processes such as viral infection, immunity, anatomical morphogenesis, and epithelial mesenchymal transition. The oxidative stress subtype was characterized by the activation of oxidative stress and various metabolic pathways and had a poor prognosis. The above results were verified independently in the validation sets. Conclusions: This study identified four molecular subtypes of BA with distinct prognosis and biological processes. According to the pathological characteristics of the different subtypes, individualized perioperative and preoperative treatment may be a new strategy to improve the prognosis of BA.

Indexed as

Biliary AtresiaCluster AnalysisHumansInfant, NewbornPrognosisTranscriptomebiliary atresiabiliary fibrosisimmunemolecular subtypesprognosis

Identifiers

PMID36713418
PMCPMC9878701

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.