Evidence map›Paper›PMID 32004343›Full record

ArticlePloS one2020

Evaluation of mitochondrial DNA copy number estimation techniques.

Ryan J Longchamps, Christina A Castellani, Stephanie Y Yang, Charles E Newcomb, Jason A Sumpter, John Lane, Megan L Grove, Eliseo Guallar, Nathan Pankratz, Kent D Taylor and 3 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed, 3 pooled it
9.1field-weighted citation impact, top 1% 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

87 citing papers in PubMed, 3 syntheses or guidelines pooled it, 153 citations in OpenAlex.

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27 more citing papers are in PubMed but not listed here.

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

13 authors at 5 institutions in 1 country.

Ryan J LongchampsDepartment of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.
Christina A CastellaniDepartment of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.ORCID 0000-0003-2737-0549
Stephanie Y YangDepartment of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.
Charles E NewcombDepartment of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.ORCID 0000-0002-2646-7288
Jason A SumpterDepartment of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.
John LaneDepartment of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States of America.
Megan L GroveHuman Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America.
Eliseo GuallarDepartment of Epidemiology and the Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States of America.
Nathan PankratzDepartment of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, United States of America.
Kent D TaylorLABioMed and Department of Pediatrics, at Harbor-UCLA Medical Center, Institute for Translational Genomics and Population Sciences, Torrance, CA, United States of America.ORCID 0000-0002-2756-4370
Jerome I RotterLABioMed and Department of Pediatrics, at Harbor-UCLA Medical Center, Institute for Translational Genomics and Population Sciences, Torrance, CA, United States of America.ORCID 0000-0001-7191-1723
Eric BoerwinkleHuman Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, United States of America.
Dan E ArkingDepartment of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America.ORCID 0000-0001-8980-8695
Johns Hopkins University · USThe Lundquist Institute · USUniversity of Minnesota Medical Center · USBaylor College of Medicine · USThe University of Texas Health Science Center at Houston · US

Funding

UCLA Clinical Translational Science InstituteUL1TR001881 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ARLEEN F. BROWN, ARASH NAEIM · 2016 to 2026
$118.1M
Institute for Clinical and Translational ResearchUL1TR001079 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2013 to 2017
$60.1M
Transgenic & Knock-out MouseP30DK063491 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PETER J TONTONOZ · 2003 to 2026
$40.4M
Technological Assessment and Solutions Core - RC4P30AG021334 · NIA · JOHNS HOPKINS UNIVERSITY · PI Jeremy D Walston · 2003 to 2026
$33.2M
Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
Clinical and Translational Science AwardUL1TR000040 · NCATS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI GINSBERG, HENRY N · 2012 to 2015
$26.2M
Predoctoral Training Program in Human GeneticsT32GM007814 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI VALLE, DAVID · 1985 to 2021
$10.6M
Mitochondrial DNA Copy Number and Genetic Variation in Coronary Heart DiseaseR01HL131573 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI ARKING, DAN E · 2016 to 2019
$3.2M
Cigarette Smoke and Susceptibility to Influenza InfectionR01HL095163 · NHLBI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI JASPERS, ILONA, NOAH, TERRY L · 2009 to 2013
$2.0M
Adjunctive Use of Apyrase to Fibrinolytic TherapyR44HL095169 · NHLBI · APT THERAPEUTICS, INC. · PI CHEN, RIDONG · 2012 to 2013
$1.3M
SLEEP AND ENTRAINMENT OF SCN FUNCTIONR01HL064278 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI STROHL, KINGMAN PERKINS · 1999 to 2002
$871k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDYN01HC095166 · HC · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · PI TRACY, RUSSELL P · 1999 to 2001
$758k
NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001881NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS HHSN268201700001CNHLBI NIH HHS HHSN268201700001INHLBI NIH HHS HHSN268201700002CNHLBI NIH HHS HHSN268201700002INHLBI NIH HHS HHSN268201700003CNHLBI NIH HHS HHSN268201700003INHLBI NIH HHS HHSN268201700004CNHLBI NIH HHS HHSN268201700004INHLBI NIH HHS HHSN268201700005CNHLBI NIH HHS HHSN268201700005INHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS N02 HL064278NHLBI NIH HHS R01 HL131573NIA NIH HHS P30 AG021334NIDDK NIH HHS P30 DK063491NIGMS NIH HHS T32 GM007814NIH HHS HHSN263201500003I
6 · The paper itself

Abstract

Mitochondrial DNA copy number (mtDNA-CN), a measure of the number of mitochondrial genomes per cell, is a minimally invasive proxy measure for mitochondrial function and has been associated with several aging-related diseases. Although quantitative real-time PCR (qPCR) is the current gold standard method for measuring mtDNA-CN, mtDNA-CN can also be measured from genotyping microarray probe intensities and DNA sequencing read counts. To conduct a comprehensive examination on the performance of these methods, we use known mtDNA-CN correlates (age, sex, white blood cell count, Duffy locus genotype, incident cardiovascular disease) to evaluate mtDNA-CN calculated from qPCR, two microarray platforms, as well as whole genome (WGS) and whole exome sequence (WES) data across 1,085 participants from the Atherosclerosis Risk in Communities (ARIC) study and 3,489 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). We observe mtDNA-CN derived from WGS data is significantly more associated with known correlates compared to all other methods (p < 0.001). Additionally, mtDNA-CN measured from WGS is on average more significantly associated with traits by 5.6 orders of magnitude and has effect size estimates 5.8 times more extreme than the current gold standard of qPCR. We further investigated the role of DNA extraction method on mtDNA-CN estimate reproducibility and found mtDNA-CN estimated from cell lysate is significantly less variable than traditional phenol-chloroform-isoamyl alcohol (p = 5.44x10-4) and silica-based column selection (p = 2.82x10-7). In conclusion, we recommend the field moves towards more accurate methods for mtDNA-CN, as well as re-analyze trait associations as more WGS data becomes available from larger initiatives such as TOPMed.

Indexed as

Gene DosageAgedDNA, MitochondrialFemaleGenomicsHumansMaleMiddle AgedDNA, Mitochondrial

Identifiers

PMID32004343
PMCPMC6994099
OpenAlexW3004176960

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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.