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BioMed Research International Volume 2019 ,2019-07-14
The Model of Aging Acceleration Network Reveals the Correlation of Alzheimer’s Disease and Aging at System Level
Research Article
Mengyu Zhou 1 Xiaoqiong Xia 1 Hao Yan 1 Sijia Li 1 Shiyu Bian 2 Xianzheng Sha 1 Yin Wang 1 , 3
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Received 2019-01-26, accepted for publication 2019-07-02, Published 2019-07-02

As the incidence of senile dementia continues to increase, researches on Alzheimer’s disease (AD) have become more and more important. Several studies have reported that there is a close relationship between AD and aging. Some researchers even pointed out that if we wanted to understand AD in depth, mechanisms of AD based on accelerated aging must be studied. Nowadays, machine learning techniques have been utilized to deal with large and complex profiles, thus playing an important role in disease researches (i.e., modelling biological systems, identifying key modules based on biological networks, and so on). Here, we developed an aging predictor and an AD predictor using machine learning techniques, respectively. Both aging and AD biomarkers were identified to provide insights into genes associated with AD. Besides, aging scores were calculated to reflect the aging process of brain tissues. As a result, the aging acceleration network and the aging-AD bipartite graph were constructed to delve into the relationship between AD and aging. Finally, a series of network and enrichment analyses were also conducted to gain further insights into the mechanisms of AD based on accelerated aging. In a word, our results indicated that aging may contribute to the development of AD by affecting the function of the immune system and the energy metabolism process, where the immune system may play a more prominent role in AD.


Copyright © 2019 Mengyu Zhou et al. 2019
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


1. Xianzheng Sha.Department of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang 110122, Liaoning Province, China, cmu.edu.cn.xzsha@cmu.edu.cn
2. Yin Wang.Department of Biomedical Engineering, School of Fundamental Sciences, China Medical University, Shenyang 110122, Liaoning Province, China, cmu.edu.cn;Tumor Etiology and Screening Department of Cancer Institute and General Surgery, The First Affiliated Hospital of China Medical University, 155# North Nanjing Street, Heping District, Shenyang 110001, Liaoning Province, China, cmu.edu.cn.chinawangyin@foxmail.com


Mengyu Zhou,Xiaoqiong Xia,Hao Yan,Sijia Li,Shiyu Bian,Xianzheng Sha,Yin Wang. The Model of Aging Acceleration Network Reveals the Correlation of Alzheimer’s Disease and Aging at System Level. BioMed Research International ,Vol.2019(2019)



[1] J. Hardy, D. J. Selkoe. (2002). The amyloid hypothesis of Alzheimer's disease: progress and problems on the road to therapeutics. Science.297(5580):353-356. DOI: 10.1126/science.1072994.
[2] A. Haapasalo, M. Pikkarainen, H. Soininen. (2015). Alzheimer's disease: a report from the 7th Kuopio Alzheimer symposium. Neurodegenerative Disease Management.5(5):379-382. DOI: 10.1126/science.1072994.
[3] C. Liu, G. Cui, M. Zhu, X. Kang. et al.(2014). Neuroinflammation in Alzheimer's disease: Chemokines produced by astrocytes and chemokine receptors. International Journal of Clinical and Experimental Pathology.7(12):8342-8355. DOI: 10.1126/science.1072994.
[4] H. Park, M.-M. Poo. (2013). Neurotrophin regulation of neural circuit development and function. Nature Reviews Neuroscience.14(1):7-23. DOI: 10.1126/science.1072994.
[5] S. Jevtic, A. S. Sengar, M. W. Salter, J. McLaurin. et al.(2017). The role of the immune system in Alzheimer disease: etiology and treatment. Ageing Research Reviews.40:84-94. DOI: 10.1126/science.1072994.
[6] Q. Zeng, R. Man, Y. Luo, L. Zeng. et al.(2017). IRF-8 is involved in Amyloid-1–40 (A1–40)-induced microglial activation: a new implication in Alzheimer’s disease. Journal of Molecular Neuroscience.63(2):159-164. DOI: 10.1126/science.1072994.
[7] V. Pons, C. Ustunel, C. Rolland, E. Torti. et al.(2012). SNX12 role in endosome membrane transport. PLoS ONE.7(6). DOI: 10.1126/science.1072994.
[8] M. J. De Leon, A. Convit, O. T. Wolf, C. Y. Tarshish. et al.(2001). Prediction of cognitive decline in normal elderly subjects with 2-[F]fluoro-2-deoxy-D-glucose/positron-emission tomography (FDG/PET). Proceedings of the National Acadamy of Sciences of the United States of America.98(19):10966-10971. DOI: 10.1126/science.1072994.
[9] D. L. Stirewalt, Y. E. Choi, N. E. Sharpless, E. L. Pogosova-Agadjanyan. et al.(2009). Decreased IRF8 expression found in aging hematopoietic progenitor/stem cells. Leukemia.23(2):391-393. DOI: 10.1126/science.1072994.
[10] S. Ohsakaya, M. Fujikawa, T. Hisabori, M. Yoshida. et al.(2011). Knockdown of DAPIT (Diabetes-associated Protein in Insulin-sensitive Tissue) results in loss of ATP synthase in mitochondria. The Journal of Biological Chemistry.286(23):20292-20296. DOI: 10.1126/science.1072994.
[11] GEO. . DOI: 10.1126/science.1072994.
[12] Y. Zhang, J. Zhang, E. Wang, W. Qian. et al.(2018). Microcystin-leucine-arginine induces tau pathology through B degradation via protein phosphatase 2A demethylation and associated glycogen synthase kinase-3 phosphorylation. Toxicological Sciences.162(2):475-487. DOI: 10.1126/science.1072994.
[13] A. M. Fjell, K. B. Walhovd, C. Fennema-Notestine, L. K. McEvoy. et al.(2009). One-year brain atrophy evident in healthy aging. The Journal of Neuroscience.29(48):15223-15231. DOI: 10.1126/science.1072994.
[14] M. Kanehisa, S. Goto, S. Kawashima, Y. Okuno. et al.(2004). The KEGG resource for deciphering the genome. Nucleic Acids Research.32:D277-D280. DOI: 10.1126/science.1072994.
[15] Z. Feng, R. W. Hanson, N. A. Berger, A. Trubitsyn. et al.(2016). Reprogramming of energy metabolism as a driver of aging. Oncotarget.7(13):15410-15420. DOI: 10.1126/science.1072994.
[16] C. B. Canto, F. G. Wouterlood, M. P. Witter. (2008). What does the anatomical organization of the entorhinal cortex tell us?. Neural Plasticity.2008-18. DOI: 10.1126/science.1072994.
[17] N. Raz, U. Lindenberger, K. M. Rodrigue, K. M. Kennedy. et al.(2005). Regional brain changes in aging healthy adults: general trends, individual differences and modifiers. Cerebral Cortex.15(11):1676-1689. DOI: 10.1126/science.1072994.
[18] C. Kawas, S. Gray, R. Brookmeyer, J. Fozard. et al.(2000). Age-specific incidence rates of Alzheimer's disease: The Baltimore longitudinal study of aging. Neurology.54(11):2072-2077. DOI: 10.1126/science.1072994.
[19] H. Antonicka, K. Choquet, Z.-Y. Lin, A.-C. Gingras. et al.(2017). A pseudouridine synthase module is essential for mitochondrial protein synthesis and cell viability. EMBO Reports.18(1):28-38. DOI: 10.1126/science.1072994.
[20] . DOI: 10.1126/science.1072994.
[21] I. Driscoll, C. Davatzikos, Y. An, X. Wu. et al.(2009). Longitudinal pattern of regional brain volume change differentiates normal aging from MCI. Neurology.72(22):1906-1913. DOI: 10.1126/science.1072994.
[22] K. Herrup. (2010). Reimagining Alzheimer's disease—an age-based hypothesis. The Journal of Neuroscience.30(50):16755-16762. DOI: 10.1126/science.1072994.
[23] L. deToledo-Morrell, T. R. Stoub, C. Wang. (2007). Hippocampal atrophy and disconnection in incipient and mild Alzheimer's disease. Progress in Brain Research.163:741-823. DOI: 10.1126/science.1072994.
[24] A. M. Fjell, L. McEvoy, D. Holland, A. M. Dale. et al.(2014). What is normal in normal aging? Effects of aging, amyloid and Alzheimer's disease on the cerebral cortex and the hippocampus. Progress in Neurobiology.117:20-40. DOI: 10.1126/science.1072994.
[25] L. Nyberg, M. Lövdén, K. Riklund, U. Lindenberger. et al.(2012). Memory aging and brain maintenance. Trends in Cognitive Sciences.16(5):292-305. DOI: 10.1126/science.1072994.
[26] . DOI: 10.1126/science.1072994.
[27] P. Chauhan, B. Saha. (2018). Metabolic regulation of infection and inflammation. Cytokine.112:1-11. DOI: 10.1126/science.1072994.
[28] G. Palmieri, E. Cocca, M. Gogliettino, R. Valentino. et al.(2017). Low erythrocyte levels of proteasome and acyl-peptide hydrolase (APEH) activities in Alzheimer's disease: a sign of defective proteostasis?. Journal of Alzheimer's Disease.60(3):1097-1106. DOI: 10.1126/science.1072994.
[29] F. Yin, H. Sancheti, I. Patil, E. Cadenas. et al.(2016). Energy metabolism and inflammation in brain aging and alzheimer’s disease. Free Radical Biology and Medicine. DOI: 10.1126/science.1072994.
[30] Q. Cai, P. Tammineni. (2017). Mitochondrial aspects of synaptic dysfunction in Alzheimer's disease. Journal of Alzheimer's Disease.57(4):1087-1103. DOI: 10.1126/science.1072994.
[31] J. M. Tarasoff-Conway, R. O. Carare, R. S. Osorio, L. Glodzik. et al.(2015). Clearance systems in the brain - implications for Alzheimer disease. Nature Reviews Neurology.11(8):457-470. DOI: 10.1126/science.1072994.
[32] P. Tammineni, Q. Cai. (2017). Defective retrograde transport impairs autophagic clearance in Alzheimer disease neurons. Autophagy.13(5):982-984. DOI: 10.1126/science.1072994.
[33] L. F. Reichardt. (2006). Neurotrophin-regulated signalling pathways. Philosophical Transactions of the Royal Society B: Biological Sciences.361(1473):1545-1564. DOI: 10.1126/science.1072994.
[34] R. Mizutani, K. Nakamura, N. Kato, K. Aizawa. et al.(2012). Expression of sorting nexin 12 is regulated in developing cerebral cortical neurons. Journal of Neuroscience Research.90(4):721-731. DOI: 10.1126/science.1072994.
[35] N. Friedman. (2004). Inferring cellular networks using probabilistic graphical models. Science.303(5659):799-805. DOI: 10.1126/science.1072994.
[36] K. G. Mawuenyega, W. Sigurdson, V. Ovod, L. Munsell. et al.(2010). Decreased clearance of CNS -amyloid in Alzheimer's disease. Science.330(6012):1774. DOI: 10.1126/science.1072994.
[37] Y. Zhao, Y. Wang, J. Yang, X. Wang. et al.(2012). Sorting nexin 12 interacts with BACE1 and regulates BACE1-mediated APP processing. Molecular Neurodegeneration.7(1, article no. 30). DOI: 10.1126/science.1072994.
[38] C. Patterson. (2018). World Alzheimer Report 2018—the state of the art of dementia research: new frontiers. . DOI: 10.1126/science.1072994.
[39] J. J. Faith, B. Hayete, J. T. Thaden, I. Mogno. et al.(2007). Large-scale mapping and validation of transcriptional regulation from a compendium of expression profiles. PLoS Biology.5(1, article no. e8). DOI: 10.1126/science.1072994.
[40] H. E. Scharfman, M. V. Chao. (2013). The entorhinal cortex and neurotrophin signaling in Alzheimer's disease and other disorders. Cognitive Neuroscience.4(3-4):123-135. DOI: 10.1126/science.1072994.
[41] S. J. Mowla, H. F. Farhadi, S. Pareek, J. K. Atwal. et al.(2001). Biosynthesis and post-translational processing of the precursor to brain-derived neurotrophic factor. The Journal of Biological Chemistry.276(16):12660-12666. DOI: 10.1126/science.1072994.
[42] K. Koivisto, K. J. Reinikainen, T. Hanninen. (1995). Prevalence of age-associated memory impairment in a randomly selected population from eastern finland. Neurology.45(4):741-747. DOI: 10.1126/science.1072994.
[43] D. M. Camacho, K. M. Collins, R. K. Powers, J. C. Costello. et al.(2018). Next-generation machine learning for biological networks. Cell.173(7):1581-1592. DOI: 10.1126/science.1072994.
[44] J. C. Morris, C. M. Roe, C. Xiong, A. M. Fagan. et al.(2010). APOE predicts amyloid-beta but not tau Alzheimer pathology in cognitively normal aging. Annals of Neurology.67(1):122-131. DOI: 10.1126/science.1072994.
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