Evidence map›Paper›PMID 38246335›Full record

ArticleMitochondrion2024

Decoding the nature and complexity of extracellular mtDNA: Types and implications for health and disease.

Andrés Caicedo, Abigail Benavides-Almeida, Alissen Haro-Vinueza, José Peña-Cisneros, Álvaro A Pérez-Meza, Jeremy Michelson, Sebastian Peñaherrera, Martin Picard

Open access · greenAbstract read
In one paragraph

Article in Mitochondrion, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
3.3field-weighted citation impact, top 8% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

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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

8 authors at 2 institutions in 2 countries.

Andrés CaicedoUniversidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina, Quito, Ecuador; Universidad San Francisco de Quito USFQ, Instituto de Investigaciones en Biomedicina iBioMed, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador; Sistemas Médicos SIME, Universidad San Francisco de Quito USFQ, Quito, Ecuador. Electronic address: acaicedo@usfq.edu.ec.
Abigail Benavides-AlmeidaUniversidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina, Quito, Ecuador; Universidad San Francisco de Quito USFQ, Instituto de Investigaciones en Biomedicina iBioMed, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador.
Alissen Haro-VinuezaUniversidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina, Quito, Ecuador; Universidad San Francisco de Quito USFQ, Instituto de Investigaciones en Biomedicina iBioMed, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador; Biología, Colegio de Ciencias Biológicas y Ambientales COCIBA, Universidad San Francisco de Quito USFQ, Quito, Ecuador.
José Peña-CisnerosUniversidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina, Quito, Ecuador; Universidad San Francisco de Quito USFQ, Instituto de Investigaciones en Biomedicina iBioMed, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador.
Álvaro A Pérez-MezaUniversidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina, Quito, Ecuador; Universidad San Francisco de Quito USFQ, Instituto de Investigaciones en Biomedicina iBioMed, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador.
Jeremy MichelsonDepartment of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, NY, USA.
Sebastian PeñaherreraUniversidad San Francisco de Quito USFQ, Colegio de Ciencias de la Salud, Escuela de Medicina, Quito, Ecuador; Universidad San Francisco de Quito USFQ, Instituto de Investigaciones en Biomedicina iBioMed, Quito, Ecuador; Mito-Act Research Consortium, Quito, Ecuador.
Martin PicardDepartment of Psychiatry, Division of Behavioral Medicine, Columbia University Irving Medical Center, New York, NY, USA; Department of Neurology, H. Houston Merritt Center, Columbia Translational Neuroscience Initiative, Columbia University Irving Medical Center, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA; Robert N Butler Columbia Aging Center, Columbia University Mailman School of Public Health, New York, NY, USA.
Universidad San Francisco de Quito · ECColumbia University Irving Medical Center · US

Funding

Transduction of Psychological Stress into Systematic Inflammation by Mitochondrial DNA SignalingR01MH119336 · NIMH · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI KAUFMAN, BRETT A, MARSLAND, ANNA L · 2019 to 2023
$3.4M
Psychobiological regulation and molecular characterization of cell-free mitochondrial DNA in humansR01MH137190 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Martin Picard, Caroline Trumpff · 2024 to 2026
$2.4M
NIMH NIH HHS R01 MH119336NIMH NIH HHS R01 MH137190
6 · The paper itself

Abstract

The mitochondrial DNA (mtDNA) is replicated and canonically functions within intracellular mitochondria, but recent discoveries reveal that the mtDNA has another exciting extracellular life. mtDNA fragments and mitochondria-containing vesicular structures are detected at high concentrations in cell-free forms, in different biofluids. Commonly referred to as cell-free mtDNA (cf-mtDNA), the field is currently without a comprehensive classification system that acknowledges the various biological forms of mtDNA and whole mitochondria existing outside the cell. This absence of classification hampers the creation of precise and consistent quantification methods across different laboratories, which is crucial for unraveling the molecular and biological characteristics of mtDNA. In this article, we integrate recent findings to propose a classification for different types of Extracellular mtDNA [ex-mtDNA]. The major biologically distinct types include: Naked mtDNA [N-mtDNA], mtDNA within non-mitochondrial Membranes [M-mtDNA], Extracellular mitochondria [exM-mtDNA], and mtDNA within Mitochondria enclosed in a Membrane [MM-mtDNA]. We outline the challenges associated with accurately quantifying these ex-mtDNA types, suggest potential physiological roles for each ex-mtDNA type, and explore how this classification could establish a foundation for future research endeavors and further analysis and definitions for ex-mtDNA. By proposing this classification of circulating mtDNA forms, we draw a parallel with the clinically recognized forms of cholesterol, such as HDL and LDL, to illustrate potential future significance in a similar manner. While not directly analogous, these mtDNA forms may one day be as biologically relevant in clinical interpretation as cholesterol fractions are currently. We also discuss how advancing methodologies to reliably quantify distinct ex-mtDNA forms could significantly enhance their utility as health or disease biomarkers, and how their application may offer innovative therapeutic approaches.

Indexed as

DNA, MitochondrialMitochondriaCholesterolCholesterolDNA, MitochondrialAgingBiomarkerClassificationExtracellular mitochondria (ex-mito)Extracellular mitochondrial DNA (ex-mtDNA)HealthIdentification methodsStressTherapeutic agent

Identifiers

PMID38246335
PMCPMC11939008
OpenAlexW4391058004

What OpenQuestion holds

Textmetadata
LicenceTDM
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.