%0 Journal Article %J J Alzheimers Dis %D 2017 %T Neuroimaging Feature Terminology: A Controlled Terminology for the Annotation of Brain Imaging Features. %A Iyappan, Anandhi %A Younesi, Erfan %A Redolfi, Alberto %A Vrooman, Henri %A Khanna, Shashank %A Frisoni, Giovanni B %A Hofmann-Apitius, Martin %X

Ontologies and terminologies are used for interoperability of knowledge and data in a standard manner among interdisciplinary research groups. Existing imaging ontologies capture general aspects of the imaging domain as a whole such as methodological concepts or calibrations of imaging instruments. However, none of the existing ontologies covers the diagnostic features measured by imaging technologies in the context of neurodegenerative diseases. Therefore, the Neuro-Imaging Feature Terminology (NIFT) was developed to organize the knowledge domain of measured brain features in association with neurodegenerative diseases by imaging technologies. The purpose is to identify quantitative imaging biomarkers that can be extracted from multi-modal brain imaging data. This terminology attempts to cover measured features and parameters in brain scans relevant to disease progression. In this paper, we demonstrate the systematic retrieval of measured indices from literature and how the extracted knowledge can be further used for disease modeling that integrates neuroimaging features with molecular processes.

%B J Alzheimers Dis %V 59 %P 1153-1169 %8 2017 %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/28731430?dopt=Abstract %R 10.3233/JAD-161148 %0 Journal Article %J J Alzheimers Dis %D 2017 %T Of Mice and Men: Comparative Analysis of Neuro-Inflammatory Mechanisms in Human and Mouse Using Cause-and-Effect Models. %A Kodamullil, Alpha Tom %A Iyappan, Anandhi %A Karki, Reagon %A Madan, Sumit %A Younesi, Erfan %A Hofmann-Apitius, Martin %X

Perturbance in inflammatory pathways have been identified as one of the major factors which leads to neurodegenerative diseases (NDD). Owing to the limited access of human brain tissues and the immense complexity of the brain, animal models, specifically mouse models, play a key role in advancing the NDD field. However, many of these mouse models fail to reproduce the clinical manifestations and end points of the disease. NDD drugs, which passed the efficacy test in mice, were repeatedly not successful in clinical trials. There are numerous studies which are supporting and opposing the applicability of mouse models in neuroinflammation and NDD. In this paper, we assessed to what extend a mouse can mimic the cellular and molecular interactions in humans at a mechanism level. Based on our mechanistic modeling approach, we investigate the failure of a neuroinflammation targeted drug in the late phases of clinical trials based on the comparative analyses between the two species.

%B J Alzheimers Dis %V 59 %P 1045-1055 %8 2017 %G eng %N 3 %1 http://www.ncbi.nlm.nih.gov/pubmed/28731442?dopt=Abstract %R 10.3233/JAD-170255 %0 Journal Article %J J Alzheimers Dis %D 2016 %T Towards a Pathway Inventory of the Human Brain for Modeling Disease Mechanisms Underlying Neurodegeneration. %A Iyappan, Anandhi %A Gündel, Michaela %A Shahid, Mohammad %A Wang, Jiali %A Li, Hui %A Mevissen, Heinz-Theodor %A Müller, Bernd %A Fluck, Juliane %A Jirsa, Viktor %A Domide, Lia %A Younesi, Erfan %A Hofmann-Apitius, Martin %X

Molecular signaling pathways have been long used to demonstrate interactions among upstream causal molecules and downstream biological effects. They show the signal flow between cell compartments, the majority of which are represented as cartoons. These are often drawn manually by scanning through the literature, which is time-consuming, static, and non-interoperable. Moreover, these pathways are often devoid of context (condition and tissue) and biased toward certain disease conditions. Mining the scientific literature creates new possibilities to retrieve pathway information at higher contextual resolution and specificity. To address this challenge, we have created a pathway terminology system by combining signaling pathways and biological events to ensure a broad coverage of the entire pathway knowledge domain. This terminology was applied to mining biomedical papers and patents about neurodegenerative diseases with focus on Alzheimer's disease. We demonstrate the power of our approach by mapping literature-derived signaling pathways onto their corresponding anatomical regions in the human brain under healthy and Alzheimer's disease states. We demonstrate how this knowledge resource can be used to identify a putative mechanism explaining the mode-of-action of the approved drug Rasagiline, and show how this resource can be used for fingerprinting patents to support the discovery of pathway knowledge for Alzheimer's disease. Finally, we propose that based on next-generation cause-and-effect pathway models, a dedicated inventory of computer-processable pathway models specific to neurodegenerative diseases can be established, which hopefully accelerates context-specific enrichment analysis of experimental data with higher resolution and richer annotations.

%B J Alzheimers Dis %V 52 %P 1343-60 %8 2016 Apr 12 %G eng %N 4 %1 http://www.ncbi.nlm.nih.gov/pubmed/27079715?dopt=Abstract %R 10.3233/JAD-151178