Pathways Analysis in Brain Aging

Nesterova, A.P.; A, K.E.; Zharkova, M.; Sobolev, V.

Авторы: Nesterova Anastasia P., Klimov Eugene A., Maria Zharkova, Vladimir Sobolev
Сборник: Precision Medicine 2017
Тезисы
Год издания: 2017
Место издания: США
DOI: 10.13140/RG.2.2.12412.74889
Аннотация: Introduction: Aging is the gradual process of destructive alterations in all structural levels of an organism, from genes and proteins to organ systems. The main difference between specific aging-related brain cells degeneration and common cell senescence seems to be a matter of the local expression: specific characteristics of differentiated tissue and cells (high number of synaptic terminals and mitochondria, unmyelinated axon) make them highly vulnerable to aging. Results: We have reconstructed “Elsevier Aging Pathways” collection (42 pathways) which is the interactive catalog containing all currently known facts about molecular bases of aging-related processes in humans, arranged in accessible format for pathway analysis of big data. The pathway is a visual map of intra-cellular interactions which contains information about proteins, small molecules, cell processes, and other entities along with relations between them. “Elsevier Aging Pathways” collection describes general molecular mechanisms of aging at the 3 levels: sub-cellular level, cell process level, and organ level and aging-related diseases such as Alzheimer disease. Parts of the collection include “mTOR Signaling and Aging”, “Proteome Instability Associated with Aging”, “Genomic Instability Associated with Aging”, “Cell Processes Associated with Aging” and “Aging Related Diseases” with total 1141 entities and 1905 number of relations. The pathway analysis is a powerful tool that can help analyzing experimental data from animal studies and personalized patients’ data and integrating the facts in the field of aging research. Pathway analysis of public microarray data showed that “Elsevier Aging Pathways” is a valid source for analyzing aging related experiments. For pathway analysis, general aging pathways and brain aging pathways were used, including “Memory Formation”, “Nociception pathways”, “Multiple Sclerosis”, “Parkinson's Disease”, “Amyotrophic Lateral Sclerosis”, “Vascular Dementia”, “Frontotemporal Dementia”, “Alzheimer's Disease” and “Sleep Dysregulation”. Conclusion: By analyzing the differentially expressed genes in animal models against our pathway collections, new candidate biomarkers likely involved in the human aging can be found. We analyzed microarray files from public GEO database and found “Traffic and Degradation of Extracellular Amyloid beta in Alzheimer's Disease” pathway as key pathway for differentially expressed genes in samples of hippocampal formation from 15-month-old mouse compare to 2-month-old young mouse. By analyzing expression data from individual patient tissue sample against our pathway collections, over or down regulated genes and new distinct molecular mechanisms can be found and considered for treatment corrections. For example, pathway analysis of public GEO microarray on human senescent astrocytes revealed “Neuro-inflammation in Astrocyte and Microglia in Lateral Sclerosis” pathway with differences and similarities in expression of genes in human senescent astrocytes and astrocytes with altered function in lateral amyotrophic sclerosis. Methods: To build the “Elsevier Aging Pathways” collection, ResNet12 database, Elsevier Pathway Studio, and Elsevier Text Mining software were used. Cheadle C, et al. Advanced literature analysis in a Big Data world. Ann N Y Acad Sci 2017;1387:25–33. doi:10.1111/nyas.13270.
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