Evidence map›Paper›PMID 41398118›Full record

ArticleMolecular neurobiology2025

miRNA Biomarkers Diagnose Amyotrophic Lateral Sclerosis in Circulating Blood.

Rachael Anne Dunlop, Paul Alan Cox, Paul Mehta, Elijah W Stommel, Sandra Anne Banack

Abstract read
In one paragraph

Article in Molecular neurobiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Rachael Anne DunlopBrain Chemistry Labs, Jackson, WY, 83001, USA.ORCID http://orcid.org/0000-0002-7816-3251
Paul Alan CoxBrain Chemistry Labs, Jackson, WY, 83001, USA.ORCID http://orcid.org/0000-0001-6401-2981
Paul MehtaOffice of Innovation and Analytics, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, 30033, USA.
Elijah W StommelDepartment of Neurology, Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA.
Sandra Anne BanackBrain Chemistry Labs, Jackson, WY, 83001, USA. sandra@brainlabs.org.ORCID http://orcid.org/0000-0001-5183-2702

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A rapid, accurate diagnostic test for amyotrophic lateral sclerosis (ALS) would reduce diagnostic delays and improve patient outcomes. We extracted eight circulating miRNAs from 788 blood plasma samples and analyzed them using qPCR for ALS diagnostic accuracy. The biomarker parameters were established previously using 449 individual blood samples and applied prospectively to an independent cohort for validation of a predictive model. The primary outcome was ALS classification accuracy as measured by diagnostic sensitivity, specificity, positive and negative predictive values (PPV, NPV), and area under the curve (AUC). The secondary outcome was comparative fold-regulation values determined prior to data collection. The diagnostic test had an AUC of 0.98 (95% CI 0.97-0.99), with 97% sensitivity (95% CI 96-98), 93% specificity (95% CI 90-96), 93% PPV (95% CI 91-96), and 97% NPV (95% CI 96-98). The fold-regulation values exceeded or were equal to prior calculated values. Streamlined methods resulted in higher diagnostic accuracy, cut both assay time and cost, reduced technical barriers, and enhances the feasibility for widespread clinical adoption. The high accuracy of this diagnostic biomarker suggests that continued evaluation is warranted.

Indexed as

Amyotrophic Lateral SclerosisMicroRNAsAdultAgedArea Under CurveBiomarkersFemaleHumansMaleMiddle AgedSensitivity and SpecificityBiomarkersMicroRNAsALS diagnostic testBlood basedHigh accuracy

Identifiers

PMID41398118
PMCPMC12705848

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Registered trials

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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.