Evidence map›Paper›PMID 28836573›Full record

ArticleNature microbiology2017

Stress and stability: applying the Anna Karenina principle to animal microbiomes.

Jesse R Zaneveld, Ryan McMinds, Rebecca Vega Thurber

Abstract read
PubMed Publisher
In one paragraph

Article in Nature microbiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 465 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
465citing papers in PubMed, 3 pooled it
29.0field-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

465 citing papers in PubMed, 3 syntheses or guidelines pooled it, 987 citations in OpenAlex.

  1. Pooled it
  2. A host of issues: pseudoreplication in host-microbiota studies.Applied and environmental microbiology · 2024
    Pooled it
  3. Pooled it
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  5. 4-1BBCell reports. Medicine · 2025
    Trial
  6. Article
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  9. Alterations of gut microbiota in Down syndrome and their association with Alzheimer's disease.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026
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405 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

3 authors at 2 institutions in 1 country.

Jesse R ZaneveldDepartment of Biological Sciences, School of Science, Technology, Education, and Mathematics, University of Washington, UWBB 249, Bothell, Washington 98011-8246, USA.
Ryan McMindsDepartment of Microbiology, Oregon State University, 226 Nash Hall, Corvallis, Oregon 97331, USA.
Rebecca Vega ThurberDepartment of Microbiology, Oregon State University, 226 Nash Hall, Corvallis, Oregon 97331, USA.
Oregon State University · USUniversity of Washington Bothell · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

All animals studied to date are associated with symbiotic communities of microorganisms. These animal microbiotas often play important roles in normal physiological function and susceptibility to disease; predicting their responses to perturbation represents an essential challenge for microbiology. Most studies of microbiome dynamics test for patterns in which perturbation shifts animal microbiomes from a healthy to a dysbiotic stable state. Here, we consider a complementary alternative: that the microbiological changes induced by many perturbations are stochastic, and therefore lead to transitions from stable to unstable community states. The result is an 'Anna Karenina principle' for animal microbiomes, in which dysbiotic individuals vary more in microbial community composition than healthy individuals-paralleling Leo Tolstoy's dictum that "all happy families look alike; each unhappy family is unhappy in its own way". We argue that Anna Karenina effects are a common and important response of animal microbiomes to stressors that reduce the ability of the host or its microbiome to regulate community composition. Patterns consistent with Anna Karenina effects have been found in systems ranging from the surface of threatened corals exposed to above-average temperatures, to the lungs of patients suffering from HIV/AIDs. However, despite their apparent ubiquity, these patterns are easily missed or discarded by some common workflows, and therefore probably underreported. Now that a substantial body of research has established the existence of these patterns in diverse systems, rigorous testing, intensive time-series datasets and improved stochastic modelling will help to explore their importance for topics ranging from personalized medicine to theories of the evolution of host-microorganism symbioses.

Indexed as

MicrobiotaStress, PhysiologicalSymbiosisAnimalsDysbiosisHumansLungMicrobial ConsortiaMicrobial InteractionsPrecision MedicineStochastic Processes

Identifiers

PMID28836573
OpenAlexW2749612575

What OpenQuestion holds

Textmetadata
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.