Evidence map›Paper›PMID 39713288›Full record

ArticlebioRxiv : the preprint server for biology2024

Gut Microbiome Signatures During Acute Infection Predict Long COVID.

Isin Y Comba, Ruben A T Mars, Lu Yang, Mitchell Dumais, Jun Chen, Trena M Van Gorp, Jonathan J Harrington, Jason P Sinnwell, Stephen Johnson, LaRinda A Holland and 8 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors.

Ruben A T Mars
Lu Yang
Mitchell Dumais
Jun Chen
Trena M Van Gorp
Jonathan J Harrington
Jason P Sinnwell
Stephen Johnson
LaRinda A Holland
Adam K Khan
Christopher Aakre
Arjun P Athreya
Jack C O'Horo
Konstantinos N Lazaridis
Purna C Kashyap

Funding

Mechanisms of alteration of GI physiology by gut microbesR01DK114007 · NIDDK · MAYO CLINIC ROCHESTER · PI Purna C Kashyap · 2017 to 2026
$4.7M
Probabilistic deep learning models and integrated biological experiments for analyzing dynamic and heterogeneous microbiomesR35GM149270 · NIGMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Georg Kurt Gerber · 2023 to 2026
$1.8M
NIDDK NIH HHS R01 DK114007NIGMS NIH HHS R35 GM149270
6 · The paper itself

Abstract

Long COVID (LC), manifests in 10-30% of non-hospitalized individuals post-SARS-CoV-2 infection leading to significant morbidity. The predictive role of gut microbiome composition during acute infection in the development of LC is not well understood, partly due to the heterogeneous nature of disease. We conducted a longitudinal study of 799 outpatients tested for SARS-CoV-2 (380 positive, 419 negative) and found that individuals who later developed LC harbored distinct gut microbiome compositions during acute infection, compared with both SARS-CoV-2-positive individuals who did not develop LC and negative controls with similar symptomatology. However, the temporal changes in gut microbiome composition between the infectious (0-1 month) and post-infectious (1-2 months) phases was not different between study groups. Using machine learning, we showed that microbiome composition alone more accurately predicted LC than clinical variables. Including clinical data only marginally enhanced this prediction, suggesting that microbiome profiles during acute infection may reflect underlying health status and immune responses thus, help predicting individuals at risk for LC. Finally, we identified four LC symptom clusters, with gastrointestinal and fatigue-only groups most strongly linked to gut microbiome alterations.

Identifiers

PMID39713288
PMCPMC11661137

What Socratic 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 Socratic graph.