Evidence map›Paper›PMID 28416017›Full record

ArticleBMC medical genomics2017

Patient complexity and genotype-phenotype correlations in biliary atresia: a cross-sectional analysis.

Guo Cheng, Patrick Ho-Yu Chung, Edwin Kin-Wai Chan, Man-Ting So, Pak-Chung Sham, Stacey S Cherny, Paul Kwong-Hang Tam, Maria-Mercè Garcia-Barceló

Open access · goldAbstract read
In one paragraph

Article in BMC medical genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 28% of its field
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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

8 authors at 2 institutions in 2 countries.

Guo ChengDepartment of Surgery, 1/F Hong Kong Jockey Club Building for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong.
Patrick Ho-Yu ChungDepartment of Surgery, 1/F Hong Kong Jockey Club Building for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong.
Edwin Kin-Wai ChanDepartment of Surgery, the Chinese University of Hong Kong, Hong Kong, SAR, China.
Man-Ting SoDepartment of Surgery, 1/F Hong Kong Jockey Club Building for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong.
Pak-Chung ShamDepartment of Psychiatry, The University of Hong Kong, Hong Kong, SAR, China.
Stacey S ChernyDepartment of Psychiatry, The University of Hong Kong, Hong Kong, SAR, China.
Paul Kwong-Hang TamDepartment of Surgery, 1/F Hong Kong Jockey Club Building for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong.
Maria-Mercè Garcia-BarcelóDepartment of Surgery, 1/F Hong Kong Jockey Club Building for Interdisciplinary Research, 5 Sassoon Road, Pokfulam, Hong Kong. mmgarcia@hku.hk.
Hong Kong Jockey Club · CNChinese University of Hong Kong · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBiliary Atresia (BA) is rare and genetically complex, and the pathogenesis is elusive. The disease course is variable and can represent heterogeneity, which hinders effective disease management. Deciphering the BA phenotypic variance is a priority in clinics and can be achieved by the integrative analysis of genotype and phenotype. We aim to explore the BA phenotypic features and to delineate the source of its variance.

methodsThe study is a cross-sectional observational study collating with case/control association analysis. One-hundred-and-eighty-one type III non-syndromic BA patients and 431 controls were included for case-control association tests, including 89 patients (47.19% males, born June 15th, 1981 to September 17th, 2007) have detailed clinical records with follow-up of the disease course (median ~17.2 years). BA-association genes from the genome-wide gene-based association test on common genetic variants (CV) and rare copy-number-variants (CNVs) from the genome-wide survey, the later comprise only CNVs > 100 kb and found in the BA patients but not in the local population (N = 1,381) or the database (N = 11,943). Hereby comorbidity is defined as a chronic disease that affects the BA patients but has no known relationship with BA or with the BA treatment. We examined genotype-phenotype correlations of CNVs, connectivity of these novel variants with BA-associated CVs, and their role in the BA candidate gene network.

resultsOf the 89 patients, 41.57% have comorbidities, including autoimmune-allergic disorders (22.47%). They carried 29 BA-private CNVs, including 3 CNVs underpinning the carriers' immunity comorbidity and one JAG1 micro-deletion. The BA-CNV-intersected genes (N = 102) and the CV-tagged genes (N = 103) were both enriched with immune-inflammatory pathway genes (FDR q < 0.20), and the two gene sets were interconnected (permutation p = 0.039). The molecular network representing CVs and rare-CNV association genes fit into a core/periphery structure, the immune genes and their related modules are found at the coherence core of all connections, suggesting its dominant role in the BA pathogenesis pathway.

conclusionsThe study highlights a patient-complexity phenomenon as a novel BA phenotypic feature, which is underpinned by rare-CNVs that biologically converge with CVs into the immune-inflammatory pathway and drives the BA occurrence and the likely BA association with immune diseases in clinics.

Indexed as

Genetic Association StudiesAdultBiliary AtresiaCase-Control StudiesComorbidityCross-Sectional StudiesDNA Copy Number VariationsFemaleGene DeletionGene Regulatory NetworksGenetic VariationHumansJagged-1 ProteinMalePolymorphism, Single NucleotideS100 ProteinsJAG1 protein, humanJagged-1 ProteinS100A13 protein, humanS100 ProteinsCopy number variantGenotype-phenotype correlationNetworkRare complex disease

Identifiers

PMID28416017
PMCPMC5392958
OpenAlexW2605966609

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Registered trials

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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.