About this Research Topic
The assessment of complex diseases is undertaken with standard clinical biochemistry assays that are frequently are insufficient to provide in depth understanding of the underlying pathological mechanisms. In contrast, omics technologies e.g. transcriptomics, proteomics and metabolomics, which have emerged in the last decade as strategies for comprehensive description of physiological as well as pathophysiological processes could be deployed to provide further insight into the complex nature of endocrine disorders. For instance, monitoring of molecular dysregulations in body fluids (blood, urine and saliva) could help in the identification of biomarkers for disease risk, identification of early stage disease as well as for monitoring of patient responses to the treatment. Furthermore, molecular dysregulations on the level of gene transcripts, proteins or metabolites could also serve as potential treatment targets. Rapidly accumulating evidence demonstrates the significant potential for the implementation of omics technologies into the field of endocrine disorders and their further translation into the clinical practice.
This Research Topic aims to provide an overview on omics strategies and solutions, which could be deployed in the field of endocrine disorders. We welcome original research, review, and mini-review articles on the different aspects of omics technologies in the pathology of endocrine disorders. Some potential topics, which are non-exclusive, include:
• Further insight into endocrine disorders driven by multi-omics analysis. The work should focus on single or combination of omics technologies to provide a more detailed description of the processes dysregulated under the endocrine disorders.
• Predictive molecular markers of endocrine disorders
• Novel therapeutic targets for the treatment of endocrine disorders revealed by omics technologies
• Molecular mechanisms of endocrine disorders
• Diagnostic perspectives of implementation of omics into the field of endocrine diseases
Keywords: Endocrine disorders, metabolomics, proteomics, transcriptomics, biomarkers
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