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

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.

Mitochondrial DNA Profiling by Fractal Lacunarity to Characterize the Senescent Phenotype as Normal Aging or Pathological Aging

“…We have recently proposed a method to characterize mtDNA mutation profile in aging and disease able to identify two main age-related neurodegenerative disorders such as Alzheimer's disease [28] and Parkinson's disease [29]. In this study, we extend the application of our lacunarity method in the study of the aging process that, following different rates, defines the senescent phenotype as physiological aging (normal rate) or pathological aging (fast rate) to confirm, in this way, that fractal analysis represents a powerful predictive/diagnostic tool based on complexity evaluation of biological structures.…”

“…Lacunarity analysis represents a more general technique as it is applicable to fractal, multi-fractal, and non-fractal (random) spatial patterns [48,49]. Regarding point mutations of mtDNA as "gaps" in the nucleotide sequence [28,29], fractal lacunarity analysis can be used to quantitatively describe the senescent phenotype that evolves lifelong as physiological or pathological aging depending on its individual specific mtDNA mutations' profile.…”

Fractal lacunarity of trabecular bone in vertebral MRI to predict osteoporotic fracture risk in over-fifties women. The LOTO study

“…An original and innovative method of MR image analysis, developed in our Institute, has been previously proposed to provide a unique parameter sensitive to TBA changes in ageing and osteoporosis [16,17]. It has been set up by considering the complexity of human beings and fractal properties of several anatomic and physiologic structures among which is bone tissue [14,[18][19][20][21][22][23]. Characterising TBA by fractal lacunarity seems to be a suitable approach.…”

Photobiomodulation for Parkinson’s Disease in Animal Models: A Systematic Review

“…Only about 15% of PD patients are likely to have a genetic cause, among which mutations in leucine-rich repeat kinase 2 (LRRK2), GBA1 (glucocerebrosidase), and SNCA (α-synuclein) are the most common [3]. The environmental causes are complex, but recent evidence has implicated mitochondrial dysfunction [4] and changes in the gut microbiome [5]. Over 1 million individuals in the US suffer from PD and the annual financial burden is estimated to be $52 billion [6].…”