Evidence map›Paper›PMID 37988592›Full record

ArticleHuman molecular genetics2024

Penetrance and expressivity of mitochondrial variants in a large clinically unselected population.

Stuart J Cannon, Timothy Hall, Gareth Hawkes, Kevin Colclough, Roisin M Boggan, Caroline F Wright, Sarah J Pickett, Andrew T Hattersley, Michael N Weedon, Kashyap A Patel

Open access · hybridAbstract read
In one paragraph

Article in Human molecular genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.4field-weighted citation impact, top 18% 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

12 citing papers in PubMed, 9 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

10 authors at 3 institutions in 1 country.

Stuart J CannonDepartment of Clinical and Biomedical Sciences, University of Exeter, 79 Heavitree Road, Exeter, EX2 4TH, United Kingdom.
Timothy HallDepartment of Clinical and Biomedical Sciences, University of Exeter, 79 Heavitree Road, Exeter, EX2 4TH, United Kingdom.
Gareth HawkesDepartment of Clinical and Biomedical Sciences, University of Exeter, 79 Heavitree Road, Exeter, EX2 4TH, United Kingdom.
Kevin ColcloughExeter Genomics Laboratory, RILD Building, Royal Devon University Healthcare NHS Foundation Trust, Barrack Road, Exeter, EX2 5DW, United Kingdom.
Roisin M BogganWellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Newcastle University, Framlington Place, Newcastle upon Tyne, NE2 4HH, United Kingdom.
Caroline F WrightDepartment of Clinical and Biomedical Sciences, University of Exeter, 79 Heavitree Road, Exeter, EX2 4TH, United Kingdom.
Sarah J PickettWellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Newcastle University, Framlington Place, Newcastle upon Tyne, NE2 4HH, United Kingdom.
Andrew T HattersleyDepartment of Clinical and Biomedical Sciences, University of Exeter, 79 Heavitree Road, Exeter, EX2 4TH, United Kingdom.
Michael N WeedonDepartment of Clinical and Biomedical Sciences, University of Exeter, 79 Heavitree Road, Exeter, EX2 4TH, United Kingdom.
Kashyap A PatelDepartment of Clinical and Biomedical Sciences, University of Exeter, 79 Heavitree Road, Exeter, EX2 4TH, United Kingdom.
University of Exeter · GBHeavitree Hospital · GBWellcome Centre for Mitochondrial Research · GB

Funding

Medical Research Council MR/T00200X/1Wellcome TrustWellcome Trust 203105/Z/16/ZWellcome Trust 204709/Z/16/ZWellcome Trust 219606/Z/19/ZWellcome Trust WT098395/Z/12/Z
6 · The paper itself

Abstract

Whole genome sequencing (WGS) from large clinically unselected cohorts provides a unique opportunity to assess the penetrance and expressivity of rare and/or known pathogenic mitochondrial variants in population. Using WGS from 179 862 clinically unselected individuals from the UK Biobank, we performed extensive single and rare variant aggregation association analyses of 15 881 mtDNA variants and 73 known pathogenic variants with 15 mitochondrial disease-relevant phenotypes. We identified 12 homoplasmic and one heteroplasmic variant (m.3243A>G) with genome-wide significant associations in our clinically unselected cohort. Heteroplasmic m.3243A>G (MAF = 0.0002, a known pathogenic variant) was associated with diabetes, deafness and heart failure and 12 homoplasmic variants increased aspartate aminotransferase levels including three low-frequency variants (MAF ~0.002 and beta~0.3 SD). Most pathogenic mitochondrial disease variants (n = 66/74) were rare in the population (<1:9000). Aggregated or single variant analysis of pathogenic variants showed low penetrance in unselected settings for the relevant phenotypes, except m.3243A>G. Multi-system disease risk and penetrance of diabetes, deafness and heart failure greatly increased with m.3243A>G level ≥ 10%. The odds ratio of these traits increased from 5.61, 12.3 and 10.1 to 25.1, 55.0 and 39.5, respectively. Diabetes risk with m.3243A>G was further influenced by type 2 diabetes genetic risk. Our study of mitochondrial variation in a large-unselected population identified novel associations and demonstrated that pathogenic mitochondrial variants have lower penetrance in clinically unselected settings. m.3243A>G was an exception at higher heteroplasmy showing a significant impact on health making it a good candidate for incidental reporting.

Indexed as

DeafnessDiabetes Mellitus, Type 2Heart FailureMitochondrial DiseasesDNA, MitochondrialHumansMutationPenetranceDNA, MitochondrialMaternally inherited diabetes and deafnessMitochondriaMitochondrial diseaseUK biobank

Identifiers

PMID37988592
PMCPMC10877468
OpenAlexW4388857462

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.