Biocomplexity and Fractality in the Search of Biomarkers of Aging and Pathology: Mitochondrial DNA Profiling of Parkinson’s Disease
Abstract
:1. Introduction
2. Results
2.1. Chaos Game Representation
2.2. Fractal Analysis of mtDNA in Aging and Parkinson’s Disease
3. Discussion
4. Materials and Methods
4.1. Subjects
4.2. mtDNA Extraction and Resequencing
4.3. Chaos Game Representation of mtDNA
- initialize A to a zero matrix having 2L rows and 2L columns,
- for each substring s⸦S, increase by one the entry of A having position p(s).
- initialize A to a zero matrix having 2L rows and 2L columns,
- for each substring s⸦S, compute the number N of multiple strings generated by the undetermined symbols in s, and perform the following cycle,
- for n=1,2,…,N,
- i.
- generate the string sn from s,
- ii.
- increase by w=1/N the entry of A having position p(sn).
- end for.
4.4. Estimate of Lacunarity
4.5. Statistical Analysis
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
AD | Alzheimer’s Disease |
ADL | Activities of Daily Living hierarchy scale |
CGR | Chaos Game Representation |
CI | Complex I |
CPS | Cognitive Performance Scale |
FD | Fractal Dimension |
GBA | Gliding Box Algorithm |
H&Y | Hoehn & Yahr stage |
mtDNA | mitochondrial DNA |
np | nucleotide position |
PD | Parkinson’s Disease |
rCRS ROS | revised Cambridge Reference Sequence Reactive Oxygen Species |
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PD Patients | Controls | |
---|---|---|
Number (M/F) | 15 (7/8) | 15 (6/9) |
Age (year) | 78.8 ± 6.0 | 80.8 ± 5.1 |
H&Y | 2.5 (2.0-3.0) | |
CPS | 2.0 (0.5-3.0) | 2.0 (0.5-2.0) |
ADL | 1.0 (0.0-2.0) | 0.0 (0.0-3.0) |
Number | rCRS | PD patients | Controls | p Value |
---|---|---|---|---|
Subjects | 15 | 15 | ||
Adenine | 5117 | 4884 ± 252 | 4912 ± 110 | 0.359 |
Cytosine | 5175 | 4658 ± 206 | 4618 ± 168 | 0.301 |
Guanine | 2163 | 2102 ± 92 | 2108 ± 49 | 0.421 |
Thymine | 4089 | 3880 ± 239 | 3916 ± 101 | 0.311 |
No-call | - | 1009 ± 765 | 980 ± 390 | 0.453 |
Homoplasmy | - | 18 ± 8 | 21 ± 8 | 0.196 |
Heteroplasmy | - | 12 ± 13 | 10 ± 6 | 0.332 |
mtDNA | whole | frame1 | ||
---|---|---|---|---|
α | β | α | β | |
rCRS | 1.6375 | 0.0053 | 1.3224 | 0.1179 |
PD patients | 1.6405 ± 0.0005 | 0.0011 ± 0.0004 | 1.3106 ± 0.060 | 0.1019 ± 0.061 |
Controls | 1.6403 ± 0.0007 | 0.0009 ± 0.0013 | 1.3150 ± 0.073 | 0.0910 ± 0.061 |
p Value | 0.179 | 0.151 | 0.433 | 0.028 |
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Zaia, A.; Maponi, P.; Zannotti, M.; Casoli, T. Biocomplexity and Fractality in the Search of Biomarkers of Aging and Pathology: Mitochondrial DNA Profiling of Parkinson’s Disease. Int. J. Mol. Sci. 2020, 21, 1758. https://doi.org/10.3390/ijms21051758
Zaia A, Maponi P, Zannotti M, Casoli T. Biocomplexity and Fractality in the Search of Biomarkers of Aging and Pathology: Mitochondrial DNA Profiling of Parkinson’s Disease. International Journal of Molecular Sciences. 2020; 21(5):1758. https://doi.org/10.3390/ijms21051758
Chicago/Turabian StyleZaia, Annamaria, Pierluigi Maponi, Martina Zannotti, and Tiziana Casoli. 2020. "Biocomplexity and Fractality in the Search of Biomarkers of Aging and Pathology: Mitochondrial DNA Profiling of Parkinson’s Disease" International Journal of Molecular Sciences 21, no. 5: 1758. https://doi.org/10.3390/ijms21051758