mtDNA diversity in human populations highlights the merit of haplotype matching in gene therapies
| Autor: | Iain G. Johnston, Ellen C. Røyrvik, Joerg P. Burgstaller |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Embryology Mitochondrial DNA Mitochondrial replacement therapy Population Single-nucleotide polymorphism Biology DNA Mitochondrial Models Biological Polymorphism Single Nucleotide Haplogroup 03 medical and health sciences 0302 clinical medicine Genetics Humans education Molecular Biology Gene education.field_of_study Haplotype Inheritance (genetic algorithm) Obstetrics and Gynecology Cell Biology Genetic Therapy QP Heteroplasmy Mitochondria 030104 developmental biology Reproductive Medicine Haplotypes Genetic distance Evolutionary biology RB 030217 neurology & neurosurgery Developmental Biology Human mitochondrial DNA haplogroup |
| Zdroj: | Europe PubMed Central |
| ISSN: | 1360-9947 |
| Popis: | STUDY QUESTION Does mitochondrial DNA (mtDNA) diversity in modern human populations potentially pose a challenge, via mtDNA segregation, to mitochondrial replacement therapies?\ud \ud 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.\ud \ud 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.\ud \ud 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.\ud \ud 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.\ud \ud 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.\ud \ud 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.\ud \ud 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. |
| Databáze: | OpenAIRE |
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