Mitochondrial DNA mutations in Parkinson's disease brain

Simon, David K.; Clark-Matott, Joanne; Espinosa, Janaina; Abraham, Neeta A.

doi:10.1186/s40478-017-0433-9

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…One limitation of studies on PD-associated mtDNA mutations is that due to the nature of the test, most of them have been performed on postmortem patient brains and thus at a late stage of the disease [28,77,78]. At this time, dopaminergic neurons in the substantia nigra that have accumulated high levels of mutations have most likely undergone cell death and are thus absent from the analysis.…”

Section: Discussionmentioning

confidence: 99%

“…We chose 6-weekold mice, the time at which brain development has completed [64] but before most PD pathological features, such as LB and motor dysfunction, are observed [47]. Based on reports that have challenged the ability of NGS to find deletions and other structural variations in mtDNA [9,[26][27][28][29][30][31], we designed an internal PC for MitoSV-seq by introducing a 4.3-kb deletion from 5930 bp to 10,395 bp into mouse mtDNA to benchmark our method (Fig. 3ab).…”

Section: Evaluation Ofmentioning

confidence: 99%

“…The detection of rare heteroplasmic variations in whole mtDNA requires extremely accurate tools to distinguish between a substantial signal and background noise. Previous studies on mtDNA have performed whole-cell sequencing, which typically includes mtDNA, or have applied a combination of long-range polymerase chain reaction (PCR), gel purification, and Sanger sequencing, resulting in the omission of low-frequency heteroplasmic mtDNA deletions [9,[26][27][28][29][30][31]. Deletions are the most common SVs in mtDNA, but some reports indicate the presence of inversions in mtDNA and their correlation with aging and mtDNA instability [32][33][34][35].…”

Section: Introductionmentioning

confidence: 99%

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Identification of unique and shared mitochondrial DNA mutations in neurodegeneration and cancer by single-cell mitochondrial DNA structural variation sequencing (MitoSV-seq)

et al. 2020

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Background: Point mutations and structural variations (SVs) in mitochondrial DNA (mtDNA) contribute to many neurodegenerative diseases. Technical limitations and heteroplasmy, however, have impeded their identification, preventing these changes from being examined in neurons in healthy and disease states. Methods: We have developed a high-resolution technique-Mitochondrial DNA Structural Variation Sequencing (MitoSV-seq)-that identifies all types of mtDNA SVs and single-nucleotide variations (SNVs) in single neurons and novel variations that have been undetectable with conventional techniques. Findings: Using MitoSV-seq, we discovered SVs/SNVs in dopaminergic neurons in the Ifnar1 À/À murine model of Parkinson disease. Further, MitoSV-seq was found to have broad applicability, delivering high-quality, full-length mtDNA sequences in a species-independent manner from human PBMCs, haematological cancers, and tumour cell lines, regardless of heteroplasmy. We characterised several common SVs in haematological cancers (AML and MDS) that were linked to the same mtDNA region, MT-ND5, using only 10 cells, indicating the power of MitoSV-seq in determining single-cancer-cell ontologies. Notably, the MT-ND5 hotspot, shared between all examined cancers and Ifnar1 À/À dopaminergic neurons, suggests that its mutations have clinical value as disease biomarkers. Interpretation: MitoSV-seq identifies disease-relevant mtDNA mutations in single cells with high resolution, rendering it a potential drug screening platform in neurodegenerative diseases and cancers.

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Section: Discussionmentioning

confidence: 99%

Section: Evaluation Ofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Identification of unique and shared mitochondrial DNA mutations in neurodegeneration and cancer by single-cell mitochondrial DNA structural variation sequencing (MitoSV-seq)

et al. 2020

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“…This could be attributable to the complexity of mitochondrial genetics and the variety of classes of mtDNA mutations relevant to neurodegenerative disease(s). Three classes of mtDNA mutations are implicated: ancient maternally inherited polymorphisms [21][22][23], recent maternally inherited pathogenic mutations [24,25], and somatic mtDNA mutations [25,26]. These last mutations accumulate in post-mitotic cells with age and amplify the biochemical effects of the former two classes.…”

Section: Introductionmentioning

confidence: 99%

Biocomplexity and Fractality in the Search of Biomarkers of Aging and Pathology: Mitochondrial DNA Profiling of Parkinson’s Disease

Alimazighi

Maponi

Zannotti

et al. 2020

IJMS

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Increasing evidence implicates mitochondrial dysfunction in the etiology of Parkinson’s disease (PD). Mitochondrial DNA (mtDNA) mutations are considered a possible cause and this mechanism might be shared with the aging process and with other age-related neurodegenerative disorders such as Alzheimer’s disease (AD). We have recently proposed a computerized method for mutated mtDNA characterization able to discriminate between AD and aging. The present study deals with mtDNA mutation-based profiling of PD. Peripheral blood mtDNA sequences from late-onset PD patients and age-matched controls were analyzed and compared to the revised Cambridge Reference Sequence (rCRS). The chaos game representation (CGR) method, modified to visualize heteroplasmic mutations, was used to display fractal properties of mtDNA sequences and fractal lacunarity analysis was applied to quantitatively characterize PD based on mtDNA mutations. Parameter β, from the hyperbola model function of our lacunarity method, was statistically different between PD and control groups when comparing mtDNA sequence frames corresponding to GenBank np 5713-9713. Our original method, based on CGR and lacunarity analysis, represents a useful tool to analyze mtDNA mutations. Lacunarity parameter β is able to characterize individual mutation profile of mitochondrial genome and could represent a promising index to discriminate between PD and aging.

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“…Consequently, the surviving neurons of late-stage PD may not differ significantly to those of aged controls with regards to mtDNA changes. Therefore, the pathological stage of disease of the patients from whom the tissue samples originated needs to be accounted for [139]. Examining neurons from early-stage (~ Braak stage 3) post-mortem tissue may be the best strategy.…”

Section: Tissue and Brain Regionmentioning

confidence: 99%

The unresolved role of mitochondrial DNA in Parkinson's disease: An overview of published studies, their limitations, and future prospects

Müller-Nedebock

Brennan

Venter

et al. 2019

Neurochemistry International

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Mitochondrial DNA mutations in Parkinson's disease brain

Cited by 7 publications

References 4 publications

Identification of unique and shared mitochondrial DNA mutations in neurodegeneration and cancer by single-cell mitochondrial DNA structural variation sequencing (MitoSV-seq)

Identification of unique and shared mitochondrial DNA mutations in neurodegeneration and cancer by single-cell mitochondrial DNA structural variation sequencing (MitoSV-seq)

Biocomplexity and Fractality in the Search of Biomarkers of Aging and Pathology: Mitochondrial DNA Profiling of Parkinson’s Disease

The unresolved role of mitochondrial DNA in Parkinson's disease: An overview of published studies, their limitations, and future prospects

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