Evidence map›Paper›PMID 41659078›Full record

ArticlemedRxiv : the preprint server for health sciences2026

ASSOCIATION ANALYSIS OF MITOCHONDRIAL HETEROPLASMIC VARIANTS AND CARDIOMETABOLIC TRAITS.

Xianbang Sun, Xue Liu, Katia Bulekova, Achilleas N Pitsillides, Xiuqing Guo, Qian Yong, Laura M Raffield, Jerome I Rotter, Stephen S Rich, Goncalo Abecasis and 12 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. 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.

No citing paper in PubMed yet.

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

22 authors.

Xianbang SunDepartment of Biostatistics, Boston University School of Public Health.
Xue LiuDepartment of Biostatistics, Boston University School of Public Health.ORCID 0000-0002-4196-3597
Katia BulekovaResearch Computing Services, Boston University, Boston, MA 02215, USA.
Achilleas N PitsillidesDepartment of Biostatistics, Boston University School of Public Health.
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, US.
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, Boston University School of Public Health.

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
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
Infrastructure for mentored access to CHS data and specimensR01HL172803 · NHLBI · UNIVERSITY OF WASHINGTON · PI James S Floyd, Michelle Christina Odden · 2025 to 2026
$2.7M
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 HL117626NHLBI NIH HHS R01 HL120393NHLBI NIH HHS R01 HL172803NHLBI NIH HHS R21 HL144877NIA NIH HHS R01 AG059727
6 · The paper itself

Abstract

Mitochondrial heteroplasmic variant has been increasingly recognized as a potential contributor to common complex diseases, yet its relationship with cardiometabolic disorders (CMDs) remains poorly understood. Leveraging deep whole-genome sequencing data from 16,882 participants across six multi-ancestry TOPMed cohorts, we systematically evaluated the associations between rare heteroplasmic variants and eight CMD traits, including body mass index (BMI), obesity, blood pressure, hypertension, blood glucose, diabetes, low-density lipoprotein (LDL), and hyperlipidemia. Using a previously developed statistical framework, we identified heteroplasmic variants according to three coding definitions and performed gene-based burden, SKAT, SKAT-O and ACAT-O tests within sixteen mitochondrial DNA (mtDNA) genes. We identified twelve significant gene-trait associations after Bonferroni correction, with consistent effect directions across coding definitions. The strongest association was observed between hyperlipidemia and heteroplasmic variants in CO1 gene (OR=0.28, 95% CI=(0.17, 0.46), p=3.4E-7) among EA (European Americans). Additional associations were detected for BMI, adjusted SBP (systolic blood pressure), BG (blood glucose), diabetes, and adjusted LDL. These findings highlight the contribution of heteroplasmic variation within mtDNA to cardiometabolic phenotypes and provide new insight into mitochondrial involvement in CMD pathophysiology.

Identifiers

PMID41659078
PMCPMC12879650

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.