Changes of protein levels in human urine reflect the dysregulation of signaling pathways of chronic kidney disease and its complications.

The increasing prevalence of chronic kidney disease (CKD) seriously is threatening human health and overall quality of life. The discovery of biomarkers of pathogenesis of CKD and the associated complications are very important for CDK diagnosis and treatment. In this paper, urine protein biomarkers were investigated because urine sample collection is convenient and non-invasive. We analyzed the protein concentrations in the urine of CKD patients and extracted abnormal protein signals comparing with the healthy control groups. The enriched signaling pathways that may characterize CKD pathology were identified from these proteins. We applied surface-enhanced laser desorption and ionization time of flight mass spectrometry technology to detect different protein peaks in urine samples from patients with CKD and healthy controls. We searched the proteins corresponding to protein peaks through the UniProt database and identified the signaling pathways of CKD and its complications by using the NIH DAVID database. 42 low abundance proteins and 46 high abundance proteins in the urine samples from CKD patients were found by comparing with healthy controls. Seven KEGG pathways related to CKD and its complications were identified from the regulated proteins. These pathways included chemokine signaling pathway, cytokine-cytokine receptor interaction, oxidative phosphorylation, cardiac muscle contraction, Alzheimer's disease, Parkinson's disease, and salivary secretion. In CKD stages 2, 3, 4, and 5, five proteins showed significantly differential abundances. The differential protein signals and regulated signaling pathways will provide new insight for the pathogenesis of CKD and its complications. These altered proteins may also be used as novel biomarkers for the noninvasive and convenient diagnosis methods of CKD and its complications through urine testing in the future.

Iron Hack - A symposium/hackathon focused on porphyrias, Friedreich's ataxia, and other rare iron-related diseases.

Background: Basic and clinical scientific research at the University of South Florida (USF) have intersected to support a multi-faceted approach around a common focus on rare iron-related diseases. We proposed a modified version of the National Center for Biotechnology Information's (NCBI) Hackathon-model to take full advantage of local expertise in building "Iron Hack", a rare disease-focused hackathon. As the collaborative, problem-solving nature of hackathons tends to attract participants of highly-diverse backgrounds, organizers facilitated a symposium on rare iron-related diseases, specifically porphyrias and Friedreich's ataxia, pitched at general audiences. Methods: The hackathon was structured to begin each day with presentations by expert clinicians, genetic counselors, researchers focused on molecular and cellular biology, public health/global health, genetics/genomics, computational biology, bioinformatics, biomolecular science, bioengineering, and computer science, as well as guest speakers from the American Porphyria Foundation (APF) and Friedreich's Ataxia Research Alliance (FARA) to inform participants as to the human impact of these diseases. Results: As a result of this hackathon, we developed resources that are relevant not only to these specific disease-models, but also to other rare diseases and general bioinformatics problems. Within two and a half days, "Iron Hack" participants successfully built collaborative projects to visualize data, build databases, improve rare disease diagnosis, and study rare-disease inheritance. Conclusions: The purpose of this manuscript is to demonstrate the utility of a hackathon model to generate prototypes of generalizable tools for a given disease and train clinicians and data scientists to interact more effectively.