Evidence map›Paper›PMID 38260412›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Association analysis of mitochondrial DNA heteroplasmic variants: methods and application.

Xianbang Sun, Katia Bulekova, Jian Yang, Meng Lai, Achilleas N Pitsillides, Xue Liu, Yuankai Zhang, Xiuqing Guo, Qian Yong, Laura M Raffield and 15 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. 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, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

25 authors at 11 institutions in 1 country.

Xianbang SunDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.
Katia BulekovaResearch Computing Services, Boston University, Boston, MA 02215, USA.
Jian YangDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.
Meng LaiDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.
Achilleas N PitsillidesDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.
Xue LiuDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.
Yuankai ZhangDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.ORCID 0000-0002-2318-7539
Xiuqing GuoThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA.
Qian YongLongitudinal Studies Section, Translational Gerontology Branch, NIA/NIH, Baltimore, MD 21224, USA.
Laura M RaffieldDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.ORCID 0000-0002-7892-193X
Jerome I RotterThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA.
Stephen S RichDepartment of Public Health Services, Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA.
Goncalo AbecasisTOPMed Informatics Research Center, University of Michigan, Ann Arbor, MI 48109, USA.
April P CarsonDepartment of Medicine, University of Mississippi Medical Center, Jackson, MS 39216, USA.
Ramachandran S VasanSections of Preventive Medicine and Epidemiology, and Cardiovascular Medicine, Boston University School of Medicine, Boston, MA, 02118, USA.
Joshua C BisCardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA.
Bruce M PsatyCardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA.
Eric BoerwinkleHuman Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Annette L FitzpatrickDepartments of Family Medicine, Epidemiology, and Global Health, University of Washington, Seattle, WA 98195, USA.
Claudia L SatizabalFramingham Heart Study, NHLBI/NIH, Framingham, MA 01702, USA.ORCID 0000-0002-1115-4430
Dan E ArkingMcKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, MD 21205, USA.
Jun DingDepartment of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
Daniel LevyFramingham Heart Study, NHLBI/NIH, Framingham, MA 01702, USA.
TOPMed mtDNA working group
Chunyu LiuDepartment of Biostatistics, School of Public Health, Boston University, Boston, MA 02118, USA.
Boston University · USUniversity of Washington · USUCLA Medical Center · USUniversity of North Carolina at Chapel Hill · USBaylor College of Medicine · USJohns Hopkins University · USNational Institutes of Health · USThe University of Texas Health Science Center at San Antonio · USUniversity of Michigan · USUniversity of Mississippi Medical Center · USUniversity of Virginia · US

Funding

Studies of Rare Genetic Variation in the Isolated Population of SardiniaR01HL117626 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2013 to 2016
$10.5M
CHARGE Consortium: Omics Discovery for CVD and Aging PhenotypesR01HL105756 · NHLBI · UNIVERSITY OF WASHINGTON · PI Bruce M Psaty, NICHOLAS L SMITH · 2011 to 2026
$9.5M
Rare variants and NHLBI traits in deeply phenotyped cohortsR01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2014 to 2016
$8.9M
Mitochondrial DNA Copy Number and Sequence Variation in Relation to Age, Alzheimer's Disease Related Phenotypes and Age-related Metabolic TraitsR01AG059727 · NIA · BOSTON UNIVERSITY MEDICAL CAMPUS · PI LIU, CHUNYU, SATIZABAL, CLAUDIA L · 2018 to 2021
$2.6M
Analysis of Heteroplasmic mtDNA Mutations in Whole Genome Sequencing: Methods and Application to Cardiometabolic Disease TraitsR21HL144877 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI LIU, CHUNYU · 2019 to 2020
$246k
NHLBI NIH HHS HHSN268201800001CNHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL117626NHLBI NIH HHS R01 HL120393NHLBI NIH HHS R21 HL144877NIA NIH HHS R01 AG059727
6 · The paper itself

Abstract

We rigorously assessed a comprehensive association testing framework for heteroplasmy, employing both simulated and real-world data. This framework employed a variant allele fraction (VAF) threshold and harnessed multiple gene-based tests for robust identification and association testing of heteroplasmy. Our simulation studies demonstrated that gene-based tests maintained an appropriate type I error rate at α=0.001. Notably, when 5% or more heteroplasmic variants within a target region were linked to an outcome, burden-extension tests (including the adaptive burden test, variable threshold burden test, and z-score weighting burden test) outperformed the sequence kernel association test (SKAT) and the original burden test. Applying this framework, we conducted association analyses on whole-blood derived heteroplasmy in 17,507 individuals of African and European ancestries (31% of African Ancestry, mean age of 62, with 58% women) with whole genome sequencing data. We performed both cohort- and ancestry-specific association analyses, followed by meta-analysis on both pooled samples and within each ancestry group. Our results suggest that mtDNA-encoded genes/regions are likely to exhibit varying rates in somatic aging, with the notably strong associations observed between heteroplasmy in the

Indexed as

association analysisgene-based testheteroplasmymitochondrial DNA sequencing

Identifiers

PMID38260412
PMCPMC10802757
OpenAlexW4390837268

What OpenQuestion holds

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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.