During the last decades, research in Alzheimer’s Disease (AD) has experienced an enormous increase in the biochemical and physiological findings of partial aspects of the disease’s evolution and its associated cognitive impairment. Within this picture, aging emerges as one of the main risk factors identified for AD, particularly for those forms of presentation termed as “Late-Onset Alzheimer’s Disease”.
However, despite some innovative attempts, the dominant approach in this field continues to be the APP/Tau-centric approach. In fact, during the last decades this reductionist approach has successfully identified the mechanisms responsible of the so-called “familial” AD (Early Onset Alzheimer Disease). But this approach offers a very limited knowledge of how system properties emerge and are disturbed under most general disease conditions as it cannot explain the etiology of so-called “sporadic” Alzheimer’s (Late-Onset AD), which represents more than 95 % of the cases in this pathology.
In sharp contrast with the dominating APP-Tau paradigm, Systems Biology encourages a comprehensive and integrative approach of such complex, multifactorial pathology. The wide range of causes and effects involved in this complex biological system would be better addressed when static or dynamic measurements are followed by data integration in some kind of mathematically formalized or computerized models. Moreover, the conclusions achieved by these models can retro-feed and give concrete criteria on which experimental working should be oriented.
Therefore, we welcome contributions from biological scientists for our Research Topic, Systems Biology Approaches to Map the Transition from Aging to Alzheimer’s Disease. We believe that this Research Topic can address both theoretical and experimental developments (e.g., how to build new, rational, experimental mouse models to map the transitions of the disease). This Topic should not be confounded with the simple use of modern technologies during the experiments, but is devoted to the effective use of this information to analyze the herein stated problem. Given that the final objective of any analysis in this field is to design an effective cure, we also welcome submissions that address the design of new therapeutic strategies that are based in previous systems biology analyses. We believe that this series of communications will prompt and stimulate the awareness of this new scientific approach to an old problem and contribute to the exchange of information among clinicians, basic scientists, mathematicians, and bioinformatics scientists.
During the last decades, research in Alzheimer’s Disease (AD) has experienced an enormous increase in the biochemical and physiological findings of partial aspects of the disease’s evolution and its associated cognitive impairment. Within this picture, aging emerges as one of the main risk factors identified for AD, particularly for those forms of presentation termed as “Late-Onset Alzheimer’s Disease”.
However, despite some innovative attempts, the dominant approach in this field continues to be the APP/Tau-centric approach. In fact, during the last decades this reductionist approach has successfully identified the mechanisms responsible of the so-called “familial” AD (Early Onset Alzheimer Disease). But this approach offers a very limited knowledge of how system properties emerge and are disturbed under most general disease conditions as it cannot explain the etiology of so-called “sporadic” Alzheimer’s (Late-Onset AD), which represents more than 95 % of the cases in this pathology.
In sharp contrast with the dominating APP-Tau paradigm, Systems Biology encourages a comprehensive and integrative approach of such complex, multifactorial pathology. The wide range of causes and effects involved in this complex biological system would be better addressed when static or dynamic measurements are followed by data integration in some kind of mathematically formalized or computerized models. Moreover, the conclusions achieved by these models can retro-feed and give concrete criteria on which experimental working should be oriented.
Therefore, we welcome contributions from biological scientists for our Research Topic, Systems Biology Approaches to Map the Transition from Aging to Alzheimer’s Disease. We believe that this Research Topic can address both theoretical and experimental developments (e.g., how to build new, rational, experimental mouse models to map the transitions of the disease). This Topic should not be confounded with the simple use of modern technologies during the experiments, but is devoted to the effective use of this information to analyze the herein stated problem. Given that the final objective of any analysis in this field is to design an effective cure, we also welcome submissions that address the design of new therapeutic strategies that are based in previous systems biology analyses. We believe that this series of communications will prompt and stimulate the awareness of this new scientific approach to an old problem and contribute to the exchange of information among clinicians, basic scientists, mathematicians, and bioinformatics scientists.