Evidence map›Paper›PMID 35577971›Full record

ArticleNature microbiology2022

Identification of shared and disease-specific host gene-microbiome associations across human diseases using multi-omic integration.

Sambhawa Priya, Michael B Burns, Tonya Ward, Ruben A T Mars, Beth Adamowicz, Eric F Lock, Purna C Kashyap, Dan Knights, Ran Blekhman

Open access · hybridAbstract read
In one paragraph

Article in Nature microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 98 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
98citing papers in PubMed, 4 pooled it
14.5field-weighted citation impact, top 1% 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

98 citing papers in PubMed, 4 syntheses or guidelines pooled it, 163 citations in OpenAlex.

  1. A host of issues: pseudoreplication in host-microbiota studies.Applied and environmental microbiology · 2024
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  17. Comparative urinary metabolomics reveals unique and shared pathways in COVID-19 and liver diseases.Metabolomics : Official journal of the Metabolomic Society · 2026
    Article
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  19. Article
  20. Article

38 more citing papers are in PubMed but not listed here.

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

9 authors at 3 institutions in 1 country.

Sambhawa PriyaDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA.
Michael B BurnsDepartment of Biology, Loyola University Chicago, Chicago, IL, USA.
Tonya WardBioTechnology Institute, College of Biological Sciences, University of Minnesota, Minneapolis, MN, USA.
Ruben A T MarsDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.
Beth AdamowiczDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA.ORCID http://orcid.org/0000-0003-3332-8021
Eric F LockDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Purna C KashyapDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Mayo Clinic, Rochester, MN, USA.ORCID http://orcid.org/0000-0002-2851-2388
Dan KnightsBioTechnology Institute, College of Biological Sciences, University of Minnesota, Minneapolis, MN, USA.
Ran BlekhmanDepartment of Genetics, Cell Biology and Development, University of Minnesota, Minneapolis, MN, USA. blekhman@umn.edu.ORCID http://orcid.org/0000-0003-3218-613X
University of Minnesota · USMayo Clinic in Arizona · USLoyola University Chicago · US

Funding

Mechanisms of alteration of GI physiology by gut microbesR01DK114007 · NIDDK · MAYO CLINIC ROCHESTER · PI Purna C Kashyap · 2017 to 2026
$4.7M
Population Genomics of Host-Microbiome InteractionsR35GM128716 · NIGMS · UNIVERSITY OF MINNESOTA · PI Ran Blekhman · 2018 to 2026
$3.5M
Identifying Biomarkers from Multi-source, Multi-way DataR01GM130622 · NIGMS · UNIVERSITY OF MINNESOTA · PI LOCK, ERIC F · 2019 to 2023
$1.5M
NIDDK NIH HHS R01 DK114007NIGMS NIH HHS R01 GM130622NIGMS NIH HHS R35 GM128716
6 · The paper itself

Abstract

While gut microbiome and host gene regulation independently contribute to gastrointestinal disorders, it is unclear how the two may interact to influence host pathophysiology. Here we developed a machine learning-based framework to jointly analyse paired host transcriptomic (n = 208) and gut microbiome (n = 208) profiles from colonic mucosal samples of patients with colorectal cancer, inflammatory bowel disease and irritable bowel syndrome. We identified associations between gut microbes and host genes that depict shared as well as disease-specific patterns. We found that a common set of host genes and pathways implicated in gastrointestinal inflammation, gut barrier protection and energy metabolism are associated with disease-specific gut microbes. Additionally, we also found that mucosal gut microbes that have been implicated in all three diseases, such as Streptococcus, are associated with different host pathways in each disease, suggesting that similar microbes can affect host pathophysiology in a disease-specific manner through regulation of different host genes. Our framework can be applied to other diseases for the identification of host gene-microbiome associations that may influence disease outcomes.

Indexed as

Gastrointestinal MicrobiomeInflammatory Bowel DiseasesMicrobiotaColonHumansIntestinal Mucosa

Identifiers

PMID35577971
PMCPMC9159953
OpenAlexW4280587540

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.