Evidence map›Paper›PMID 38872308›Full record

ArticleHGG advances2024

Identifying dysregulated regions in amyotrophic lateral sclerosis through chromatin accessibility outliers.

Muhammed Hasan Çelik, Julien Gagneur, Ryan G Lim, Jie Wu, Leslie M Thompson, Xiaohui Xie

Abstract read
In one paragraph

Article in HGG advances, 2024. 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
–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

2 citing papers in PubMed.

  1. Population-scale detection of methylation outliers from long-read genome sequencing.medRxiv : the preprint server for health sciences · 2026
    Article
  2. Article
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

6 authors.

Muhammed Hasan ÇelikDepartment of Computer Science, University of California Irvine, Irvine, CA, USA; Center for Complex Biological Systems, University of California Irvine, Irvine, CA, USA.
Julien GagneurDepartment of Informatics, Technical University of Munich, Garching, Germany; Helmholtz Association - Munich School for Data Science (MUDS), Munich, Germany; Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany; Institute of Computational Biology, Helmholtz Center Munich, Neuherberg, Germany.
Ryan G LimInstitute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine, CA 92697, USA.
Jie WuDepartment of Biological Chemistry, University of California Irvine, Irvine, CA, USA.
Leslie M ThompsonInstitute for Memory Impairments and Neurological Disorders, University of California Irvine, Irvine, CA 92697, USA; Department of Biological Chemistry, University of California Irvine, Irvine, CA, USA; UCI MIND, University of California Irvine, Irvine, CA, USA; Department of Psychiatry and Human Behavior and Sue and Bill Gross Stem Cell Center, University of California Irvine, Irvine, CA, USA; Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, USA.
Xiaohui XieDepartment of Computer Science, University of California Irvine, Irvine, CA, USA. Electronic address: xhx@ics.uci.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The high heritability of amyotrophic lateral sclerosis (ALS) contrasts with its low molecular diagnosis rate post-genetic testing, pointing to potential undiscovered genetic factors. To aid the exploration of these factors, we introduced EpiOut, an algorithm to identify chromatin accessibility outliers that are regions exhibiting divergent accessibility from the population baseline in a single or few samples. Annotation of accessible regions with histone chromatin immunoprecipitation sequencing and Hi-C indicates that outliers are concentrated in functional loci, especially among promoters interacting with active enhancers. Across different omics levels, outliers are robustly replicated, and chromatin accessibility outliers are reliable predictors of gene expression outliers and aberrant protein levels. When promoter accessibility does not align with gene expression, our results indicate that molecular aberrations are more likely to be linked to post-transcriptional regulation rather than transcriptional regulation. Our findings demonstrate that the outlier detection paradigm can uncover dysregulated regions in rare diseases. EpiOut is available at github.com/uci-cbcl/EpiOut.

Indexed as

Amyotrophic Lateral SclerosisChromatinAlgorithmsChromatin Immunoprecipitation SequencingGene Expression RegulationHistonesHumansPromoter Regions, GeneticChromatinHistonesAberrant Gene ExpressionAmyotrophic Lateral Sclerosis (ALS)Chromatin AccessibilityEpigeneticsMotor Neuron DiseaseMultiomicsOutlier DetectionPost-transcriptional RegulationRare DiseaseTranscriptional Regulation

Identifiers

PMID38872308
PMCPMC11260578

What OpenQuestion holds

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Registered trials

None linked

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.