Go to The Journal of Clinical Investigation
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact
  • Physician-Scientist Development
  • Current issue
  • Past issues
  • By specialty
    • COVID-19
    • Cardiology
    • Immunology
    • Metabolism
    • Nephrology
    • Oncology
    • Pulmonology
    • All ...
  • Videos
  • Collections
    • In-Press Preview
    • Resource and Technical Advances
    • Clinical Research and Public Health
    • Research Letters
    • Editorials
    • Perspectives
    • Physician-Scientist Development
    • Reviews
    • Top read articles

  • Current issue
  • Past issues
  • Specialties
  • In-Press Preview
  • Resource and Technical Advances
  • Clinical Research and Public Health
  • Research Letters
  • Editorials
  • Perspectives
  • Physician-Scientist Development
  • Reviews
  • Top read articles
  • About
  • Editors
  • Consulting Editors
  • For authors
  • Publication ethics
  • Publication alerts by email
  • Transfers
  • Advertising
  • Job board
  • Contact

Submit a comment

α-Diversity analysis of hepatic transcriptome reveals distinct pathways in alcohol-associated hepatitis
Sudrishti Chaudhary, Jia-Jun Liu, Silvia Liu, Marissa Di, Juliane I. Beier, Ramon Bataller, Josepmaria Argemi, Panayiotis V. Benos, Gavin E. Arteel
Sudrishti Chaudhary, Jia-Jun Liu, Silvia Liu, Marissa Di, Juliane I. Beier, Ramon Bataller, Josepmaria Argemi, Panayiotis V. Benos, Gavin E. Arteel
View: Text | PDF
Research Article Hepatology Inflammation

α-Diversity analysis of hepatic transcriptome reveals distinct pathways in alcohol-associated hepatitis

  • Text
  • PDF
Abstract

Next-generation sequencing can identify previously uncharacterized gene expression patterns in disease. Beyond differentially expressed gene (DEG) analysis, we investigated the ability of within-population diversity (α-diversity) of the transcriptome to reveal additional biological information in alcohol-associated liver disease (ALD), comparing differential Shannon diversity (DSD) to transcriptome heterogeneity changes. RNA sequencing data from normal livers and patients with early ALD and severe AH were analyzed. α-Diversity indices and percentage Shannon diversity of a gene, which refers to this gene’s contribution to total Shannon entropy, were calculated. Ingenuity pathway analysis identified canonical pathways determined by DEG and DSD approaches. ALD significantly decreased hepatic transcriptome α-diversity, correlating with increased relative contribution of select genes. These changes were driven by lower-abundance gene expression loss. DEG and DSD analyses showed overlapping genes and canonical pathways, but DSD also identified additional genes and pathways not highlighted by DEGs, including fatty acid oxidation, extracellular matrix degradation, and cholesterol metabolism pathways that may represent additional therapeutic targets. Importantly, DSD more effectively identified differences between ASH and AH. Overall, α-diversity analysis revealed that ALD progressively reduces transcriptome heterogeneity, and that DSD provides complementary insights into disease mechanisms missed by standard approaches.

Authors

Sudrishti Chaudhary, Jia-Jun Liu, Silvia Liu, Marissa Di, Juliane I. Beier, Ramon Bataller, Josepmaria Argemi, Panayiotis V. Benos, Gavin E. Arteel

×

Guidelines

The Editorial Board will only consider comments that are deemed relevant and of interest to readers. The Journal will not post data that have not been subjected to peer review; or a comment that is essentially a reiteration of another comment.

  • Comments appear on the Journal’s website and are linked from the original article’s web page.
  • Authors are notified by email if their comments are posted.
  • The Journal reserves the right to edit comments for length and clarity.
  • No appeals will be considered.
  • Comments are not indexed in PubMed.

Specific requirements

  • Maximum length, 400 words
  • Entered as plain text or HTML
  • Author’s name and email address, to be posted with the comment
  • Declaration of all potential conflicts of interest (even if these are not ultimately posted); see the Journal’s conflict-of-interest policy
  • Comments may not include figures
This field is required
This field is required
This field is required
This field is required
This field is required
This field is required

Copyright © 2026 American Society for Clinical Investigation
ISSN 2379-3708

Sign up for email alerts