Literature DB >> 27609757

mtDNA diversity in human populations highlights the merit of haplotype matching in gene therapies.

E C Røyrvik1, J P Burgstaller2,3, I G Johnston4.   

Abstract

STUDY QUESTION: Does mitochondrial DNA (mtDNA) diversity in modern human populations potentially pose a challenge, via mtDNA segregation, to mitochondrial replacement therapies? SUMMARY ANSWER: The magnitude of mtDNA diversity in modern human populations is as high as in mammalian model systems where strong mtDNA segregation is observed; consideration of haplotype pairs and/or haplotype matching can help avoid these potentially deleterious effects. WHAT IS KNOWN ALREADY: In mammalian models, substantial proliferative differences are observed between different mtDNA haplotypes in cellular admixtures, with larger proliferative differences arising from more diverse haplotype pairings. If maternal mtDNA is 'carried over' in human gene therapies, these proliferative differences could lead to its amplification in the resulting offspring, potentially leading to manifestation of the disease that the therapy was designed to avoid-but existing studies have not investigated whether mtDNA diversity in modern human populations is sufficient to permit significant amplification. STUDY DESIGN, SIZE, DURATION: This theoretical study used over 7500 human mtDNA sequences from The National Center for Biotechnology Information (NCBI), a range of international and British mtDNA surveys, and 2011 census data. PARTICIPANTS/MATERIALS, SETTING,
METHODS: A stochastic simulation approach was used to model random haplotype pairings from within different regions. In total, 1000 simulated pairings were analysed using the basic local alignment search tool (BLAST) for each region. Previous data from mouse models were used to estimate proliferative differences. MAIN RESULTS AND THE ROLE OF CHANCE: Even within the same haplogroup, differences of around 20-80 single-nucleotide polymorphisms (SNPs) are common between mtDNAs admixed in random pairings. These values are sufficient to lead to substantial segregation in mouse models over an organismal lifetime, even given low starting heteroplasmy, inducing increases from 5% to 35% over 1 year. Substantial population mixing in modern UK cities increases the expected genetic differences. Hence, the likely genetic differences between humans randomly sampled from a population may well allow substantial amplification of a disease-carrying mtDNA haplotype over the timescale of a human lifetime. We report ranges and mean differences for all statistics to quantify uncertainty in our results. LIMITATIONS/REASONS FOR CAUTION: The mapping from mouse and other mammalian models to the human system is challenging, as timescales and mechanisms may differ. Reporting biases in NCBI mtDNA data, if present, may affect the statistics we compute. We discuss the robustness of our findings in the light of these concerns. WIDER IMPLICATIONS OF THE
FINDINGS: Matching the mtDNA haplotypes of the mother and third-party donor in mitochondrial replacement therapies is supported as a means of ameliorating the potentially deleterious results of human mtDNA diversity. We present a chart of expected SNP differences between mtDNA haplogroups, allowing the selection of optimal partners for therapies. LARGE SCALE DATA: N/A STUDY FUNDING/COMPETING INTERESTS: The authors report no external funding sources or conflicts of interest.
© The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  gene therapy; haplotype matching; human populations; mitochondrial DNA; mitochondrial replacement therapy; mtDNA; segregation bias

Mesh:

Substances:

Year:  2016        PMID: 27609757     DOI: 10.1093/molehr/gaw062

Source DB:  PubMed          Journal:  Mol Hum Reprod        ISSN: 1360-9947            Impact factor:   4.025


  11 in total

1.  Toward Precision Healthcare: Context and Mathematical Challenges.

Authors:  Caroline Colijn; Nick Jones; Iain G Johnston; Sophia Yaliraki; Mauricio Barahona
Journal:  Front Physiol       Date:  2017-03-21       Impact factor: 4.566

2.  Threading Granules in Freiburg. 2nd International Symposium on "One Mitochondrion, Many Diseases - Biological and Molecular Perspectives", a FRIAS Junior Researcher Conference, Freiburg im Breisgau, Germany, March 9th/10th, 2016.

Authors:  Ralf J Braun; Ralf M Zerbes; Florian Steinberg; Denis Gris; Verónica I Dumit
Journal:  Microb Cell       Date:  2016-11-04

3.  MtDNA sequence features associated with 'selfish genomes' predict tissue-specific segregation and reversion.

Authors:  Ellen C Røyrvik; Iain G Johnston
Journal:  Nucleic Acids Res       Date:  2020-09-04       Impact factor: 16.971

4.  Large-scale genetic analysis reveals mammalian mtDNA heteroplasmy dynamics and variance increase through lifetimes and generations.

Authors:  Joerg P Burgstaller; Thomas Kolbe; Vitezslav Havlicek; Stephanie Hembach; Joanna Poulton; Jaroslav Piálek; Ralf Steinborn; Thomas Rülicke; Gottfried Brem; Nick S Jones; Iain G Johnston
Journal:  Nat Commun       Date:  2018-06-27       Impact factor: 14.919

5.  Matching Mitochondrial DNA Haplotypes for Circumventing Tissue-Specific Segregation Bias.

Authors:  Jianxin Pan; Li Wang; Charles Lu; Yanming Zhu; Zhunyuan Min; Xi Dong; Hongying Sha
Journal:  iScience       Date:  2019-03-05

6.  Energetic costs of cellular and therapeutic control of stochastic mitochondrial DNA populations.

Authors:  Hanne Hoitzing; Payam A Gammage; Lindsey Van Haute; Michal Minczuk; Iain G Johnston; Nick S Jones
Journal:  PLoS Comput Biol       Date:  2019-06-26       Impact factor: 4.475

Review 7.  Evolving mtDNA populations within cells.

Authors:  Iain G Johnston; Joerg P Burgstaller
Journal:  Biochem Soc Trans       Date:  2019-10-31       Impact factor: 5.407

8.  Mitochondrial DNA Haplogroups and Breast Cancer Risk Factors in the Avon Longitudinal Study of Parents and Children (ALSPAC).

Authors:  Vivienne Riley; A Mesut Erzurumluoglu; Santiago Rodriguez; Carolina Bonilla
Journal:  Genes (Basel)       Date:  2018-08-01       Impact factor: 4.096

Review 9.  Not all mitochondrial DNAs are made equal and the nucleus knows it.

Authors:  Ana Victoria Lechuga-Vieco; Raquel Justo-Méndez; José Antonio Enríquez
Journal:  IUBMB Life       Date:  2020-12-25       Impact factor: 3.885

10.  Cell reprogramming shapes the mitochondrial DNA landscape.

Authors:  Wei Wei; Daniel J Gaffney; Patrick F Chinnery
Journal:  Nat Commun       Date:  2021-09-02       Impact factor: 14.919

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