Evidence map›Paper›PMID 34718574›Full record

ArticleHuman molecular genetics2022

First mitochondrial genome-wide association study with metabolomics.

Brahim Aboulmaouahib, Gabi Kastenmüller, Karsten Suhre, Sebastian Zöllner, Hansi Weissensteiner, Cornelia Prehn, Jerzy Adamski, Christian Gieger, Rui Wang-Sattler, Peter Lichtner and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Human molecular genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.0field-weighted citation impact, top 25% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Use of Mendelian Randomization to Unveil Metabolic Markers inJournal of Korean medical science · 2026
    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

12 authors at 7 institutions in 6 countries.

Brahim AboulmaouahibInstitute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU, Munich, Germany.ORCID 0000-0002-9231-8168
Gabi KastenmüllerInstitute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Karsten SuhreDepartment of Physiology and Biophysics, Weill Cornell Medical College in Qatar, Qatar, State of Qatar.
Sebastian ZöllnerDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
Hansi WeissensteinerDepartment of Genetics and Pharmacology, Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
Cornelia PrehnMetabolomics and Proteomics Core, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Jerzy AdamskiInstitute of Experimental Genetics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Christian GiegerResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Rui Wang-SattlerResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Peter LichtnerInstitute of Human Genetics, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
Konstantin StrauchInstitute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU, Munich, Germany.
Antònia FlaquerInstitute for Medical Information Processing, Biometry and Epidemiology-IBE, LMU, Munich, Germany.
Helmholtz Zentrum München · DEJohannes Gutenberg University Mainz · DENational University of Singapore · SGInnsbruck Medical University · ATUniversity of Ljubljana · SIUniversity of Michigan · USWeill Cornell Medical College in Qatar · QA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the era of personalized medicine with more and more patient-specific targeted therapies being used, we need reliable, dynamic, faster and sensitive biomarkers both to track the causes of disease and to develop and evolve therapies during the course of treatment. Metabolomics recently has shown substantial evidence to support its emerging role in disease diagnosis and prognosis. Aside from biomarkers and development of therapies, it is also an important goal to understand the involvement of mitochondrial DNA (mtDNA) in metabolic regulation, aging and disease development. Somatic mutations of the mitochondrial genome are also heavily implicated in age-related disease and aging. The general hypothesis is that an alteration in the concentration of metabolite profiles (possibly conveyed by lifestyle and environmental factors) influences the increase of mutation rate in the mtDNA and thereby contributes to a range of pathophysiological alterations observed in complex diseases. We performed an inverted mitochondrial genome-wide association analysis between mitochondrial nucleotide variants (mtSNVs) and concentration of metabolites. We used 151 metabolites and the whole sequenced mitochondrial genome from 2718 individuals to identify the genetic variants associated with metabolite profiles. Because of the high coverage, next-generation sequencing-based analysis of the mitochondrial genome allows for an accurate detection of mitochondrial heteroplasmy and for the identification of variants associated with the metabolome. The strongest association was found for mt715G > A located in the MT-12SrRNA with the metabolite ratio of C2/C10:1 (P-value = 6.82*10-09, β = 0.909). The second most significant mtSNV was found for mt3714A > G located in the MT-ND1 with the metabolite ratio of phosphatidylcholine (PC) ae C42:5/PC ae C44:5 (P-value = 1.02*10-08, β = 3.631). A large number of significant metabolite ratios were observed involving PC aa C36:6 and the variant mt10689G > A, located in the MT-ND4L gene. These results show an important interconnection between mitochondria and metabolite concentrations. Considering that some of the significant metabolites found in this study have been previously related to complex diseases, such as neurological disorders and metabolic conditions, these associations found here might play a crucial role for further investigations of such complex diseases. Understanding the mechanisms that control human health and disease, in particular, the role of genetic predispositions and their interaction with environmental factors is a prerequisite for the development of safe and efficient therapies for complex disorders.

Indexed as

Genome-Wide Association StudyMetabolomicsBiomarkersDNA, MitochondrialHumansMitochondriaNucleotidesPhosphatidylcholinesBiomarkersDNA, MitochondrialNucleotidesPhosphatidylcholines

Identifiers

PMID34718574
PMCPMC9523559
OpenAlexW3209142412

What OpenQuestion 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 OpenQuestion graph.