Evidence map›Paper›PMID 35074858›Full record

ArticleGenome research2022

Mitochondrial DNA variation across 56,434 individuals in gnomAD.

Kristen M Laricchia, Nicole J Lake, Nicholas A Watts, Megan Shand, Andrea Haessly, Laura Gauthier, David Benjamin, Eric Banks, Jose Soto, Kiran Garimella and 8 more

Abstract read
In one paragraph

Article in Genome research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 87 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
87citing papers in PubMed, 1 pooled it
–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

87 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

18 authors.

Kristen M Laricchia *Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Nicole J Lake *Yale School of Medicine, New Haven, Connecticut 06510, USA.ORCID 0000-0003-4103-6387
Nicholas A WattsBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Megan ShandBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Andrea HaesslyBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.ORCID 0000-0002-8583-4711
Laura GauthierBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
David BenjaminBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Eric BanksBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Jose SotoBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Kiran GarimellaBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.ORCID 0000-0002-6212-5736
James EmeryBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Genome Aggregation Database Consortium
Heidi L RehmBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.ORCID 0000-0002-6025-0015
Daniel G MacArthurBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.ORCID 0000-0002-5771-2290
Grace TiaoBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.
Monkol LekYale School of Medicine, New Haven, Connecticut 06510, USA.
Vamsi K MoothaBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.ORCID 0000-0001-9924-642X
Sarah E CalvoBroad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.ORCID 0000-0001-6449-6058

Funding

The Genome Aggregation Database (gnomAD)U24HG011450 · NHGRI · BROAD INSTITUTE, INC. · PI Mark Joseph Daly, Konrad Karczewski · 2021 to 2026
$22.3M
Computational resources for genomic interpretation of type 2 diabetesU54DK105566 · NIDDK · BROAD INSTITUTE, INC. · PI MACARTHUR, DANIEL G, NEALE, BENJAMIN MICHAEL · 2014 to 2017
$8.6M
Mitochondrial Parts, Pathways, and PathogenesisR35GM122455 · NIGMS · BROAD INSTITUTE, INC. · PI MOOTHA, VAMSI KRISHNA · 2017 to 2021
$4.0M
NHGRI NIH HHS U24 HG011450NIDDK NIH HHS U54 DK105566NIGMS NIH HHS R35 GM122455
6 · The paper itself

Abstract

Genomic databases of allele frequency are extremely helpful for evaluating clinical variants of unknown significance; however, until now, databases such as the Genome Aggregation Database (gnomAD) have focused on nuclear DNA and have ignored the mitochondrial genome (mtDNA). Here, we present a pipeline to call mtDNA variants that addresses three technical challenges: (1) detecting homoplasmic and heteroplasmic variants, present, respectively, in all or a fraction of mtDNA molecules; (2) circular mtDNA genome; and (3) misalignment of nuclear sequences of mitochondrial origin (NUMTs). We observed that mtDNA copy number per cell varied across gnomAD cohorts and influenced the fraction of NUMT-derived false-positive variant calls, which can account for the majority of putative heteroplasmies. To avoid false positives, we excluded contaminated samples, cell lines, and samples prone to NUMT misalignment due to few mtDNA copies. Furthermore, we report variants with heteroplasmy ≥10%. We applied this pipeline to 56,434 whole-genome sequences in the gnomAD v3.1 database that includes individuals of European (58%), African (25%), Latino (10%), and Asian (5%) ancestry. Our gnomAD v3.1 release contains population frequencies for 10,850 unique mtDNA variants at more than half of all mtDNA bases. Importantly, we report frequencies within each nuclear ancestral population and mitochondrial haplogroup. Homoplasmic variants account for most variant calls (98%) and unique variants (85%). We observed that 1/250 individuals carry a pathogenic mtDNA variant with heteroplasmy above 10%. These mtDNA population allele frequencies are freely accessible and will aid in diagnostic interpretation and research studies.

Indexed as

DNA, MitochondrialGenome, MitochondrialCell NucleusGene FrequencyGenomeHumansMitochondriaSequence Analysis, DNADNA, Mitochondrial

Identifiers

PMID35074858
PMCPMC8896463

What OpenQuestion holds

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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.