Abstract
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.
Highlights
Parkinson’s disease (PD) is a neurodegenerative disorder with heavily age-dependent prevalence affecting 1% of over 65s and more than 4% of over 85s subjects worldwide [1]
We have recently proposed a method of lacunarity analysis of chaos game representation (CGR) of Mitochondrial DNA (mtDNA) sequences [33] able to discriminate between aging and Alzheimer’s disease (AD) on the basis of mtDNA mutation profiles
Any set of matrices 2Lx2L was analyzed to verify the potential of our lacunarity parameter β in characterizing alterations of mtDNA in aging and PD, based on the revised Cambridge Reference Sequence
Summary
Parkinson’s disease (PD) is a neurodegenerative disorder with heavily age-dependent prevalence affecting 1% of over 65s and more than 4% of over 85s subjects worldwide [1]. Over the past two decades, scientific opinion has varied between two positions in which only environmental factors or only genetic factors were considered to be dominant [2,3,4,5,6,7]. The interest for the genetic implication in the pathogenesis of PD has been increasing. The role of abnormal protein processing has been recognized as a major mechanism of cell death in both genetic and sporadic PD as well as in other neurodegenerative disorders [10,11]
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