Evidence map›Paper›PMID 38295557›Full record

ReviewNeurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics2024

Biomarkers of mitochondrial disorders.

Brian J Shayota

Abstract readReview
In one paragraph

Review in Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

1 author.

Brian J ShayotaDivision of Medical Genetics, Department of Pediatrics, University of Utah, Salt Lake City, UT, USA. Electronic address: brian.shayota@hsc.utah.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mitochondrial diseases encompass a heterogeneous group of disorders with a wide range of clinical manifestations, most classically resulting in neurological, muscular, and metabolic abnormalities, but having the potential to affect any organ system. Over the years, substantial progress has been made in identifying and characterizing various biomarkers associated with mitochondrial diseases. This review summarizes the current knowledge of mitochondrial biomarkers based on a literature review and discusses the evidence behind their use in clinical practice. A total of 13 biomarkers were thoroughly reviewed including lactate, pyruvate, lactate:pyruvate ratio, creatine kinase, creatine, amino acid profiles, glutathione, malondialdehyde, GDF-15, FGF-21, gelsolin, neurofilament light-chain, and circulating cell-free mtDNA. Most biomarkers had mixed findings depending on the study, especially when considering their utility for specific mitochondrial diseases versus mitochondrial conditions in general. However, in large biomarker comparison studies, GDF-15 followed by FGF-21, seem to have the greatest value though they are still not perfect. As such, additional studies are needed, especially in light of newer biomarkers that have not yet been thoroughly investigated. Understanding the landscape of biomarkers in mitochondrial diseases is crucial for advancing early detection, improving patient management, and developing targeted therapies.

Indexed as

Growth Differentiation Factor 15Mitochondrial DiseasesBiomarkersDNA, MitochondrialHumansLactic AcidPyruvic AcidBiomarkersDNA, MitochondrialGrowth Differentiation Factor 15Lactic AcidPyruvic AcidBiomarkerMitochondrial diseaseMitochondrial dysfunction

Identifiers

PMID38295557
PMCPMC10903091

What OpenQuestion holds

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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.