Evidence map›Paper›PMID 40236248›Full record

ArticlebioRxiv : the preprint server for biology2025

Optimizing Protocols for MicroRNA Profiling of Infant and Toddler Stool.

David A Armstrong, Shannon M Soucy, Meghan E Muse, Fred W Kolling, Heidi W Trask, Alexandra L Howell, Hannah E Laue, Anne G Hoen, Jiang Gui, Brock C Christensen and 3 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

David A ArmstrongORCID 0000-0003-1748-2520
Meghan E Muse
Heidi W Trask
Alexandra L HowellORCID 0000-0002-2362-2596
Anne G Hoen
Jiang Gui
Brock C ChristensenORCID 0000-0003-3022-426X
Juliette C Madan
Margaret R Karagas

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI MICHAEL L WHITFIELD · 2019 to 2026
$27.2M
NCI NIH HHS P30 CA023108NIGMS NIH HHS P20 GM130454
6 · The paper itself

Abstract

Background: MicroRNAs (miRNAs) are increasingly being investigated as potential biomarkers for child development and disease. Although a growing number of studies are utilizing infant and toddler stool for transcriptomic analyses, no studies have compared protocols for preserving and extracting miRNAs from this specimen type, despite unique challenges, including abundant levels of RNAses and microbial RNA. Methods: To address this, we first compared three commercially available kits and four preservation methods for their ability to yield high quality RNA from infant and toddler stool (Phase 1). RNA quality was determined by fragment analyzer. Results: Of the three RNA extraction kits compared, Zymo BIOMICs yielded the highest overall RNA Quality Number (RQN) (median (range) RQN 9.4 (5.7-10.0)). Of the four preservation methods tested, stool collected in RNAlater and Zymo DNA/RNA Shield Fecal Collection Tubes yielded the highest two RQNs (median (range) RQN 9.8 (5.7-10.0) and 9.4 (5.4-10.0), respectively), which did not differ significantly from each other ( Conclusions: Collecting infant and toddler stool in either RNAlater or Zymo DNA/RNA Shield Fecal Collection Tubes, when paired with RNA extraction using the Zymo BIOMICs extraction kit, yielded high-quality RNA with similar human miRNA profiles. Moreover, of the 42 miRNAs that were detected, several (i.e., miR-194a-3p, miR-200c-3p, miR-26a-5p) are thought to contribute to overall gut homeostasis. These findings may inform protocols for future studies that aim to profile miRNAs in infant and toddler stool to evaluate their potential utility as biomarkers for children's health.

Identifiers

PMID40236248
PMCPMC11996525

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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.