Abstract
Background: At present, the main diagnostic methods for Alzheimer's disease (AD) are positron emission tomography (PET) scanning of the brain and analysis of cerebrospinal fluid (CSF) sample, but these methods are expensive and harmful to patients. Recently, more researchers focus on diagnosing AD by detecting biomarkers in blood, which is a cheaper and harmless way. Therefore, identifying AD-related proteins in blood can help treatment and diagnosis.Methods: We proposed a hypothesis that similar diseases share similar proteins. Diseases with similar symptoms are caused by abnormalities of similar proteins. Assuming that the similarities between AD and other diseases obey the normal distribution, we developed an iterative method based on disease similarity (IBDS). We combined Elastic Network (EN) with Minimum angle regression (MAR) to find the optimal solution. Finally, we used case studies and Summary data Mendelian Random (SMR) to verify our method.Results: We selected 39 diseases which are highly related to AD. They correspond 1,481 kinds of proteins. One hundred and eighty-four proteins are reported to be related to AD in Uniprot and the number would be 284 with our method. The AUC of our method by cross-validation is 0.9251 which is much higher than previous methods.Conclusion: In this paper, we presented a novel method for prioritizing AD-related proteins. Seven proteins have tissue specificity in blood among these 284 proteins, which could be used to diagnose AD in future. Case studies and SMR have been used to prove the relationship between these 7 proteins and AD.Availability and Implementation: https://github.com/zty2009/Identifying-Protein-Biomarkers-in-Blood-for-Alzheimer-s-Disease
Highlights
Alzheimer’s disease (AD) is a progressive neurodegenerative disease with insidious onset (Peng and Zhao, 2020)
We want to know how many proteins we have found to be related to AD
With the prolongation of human life span, more and more people are suffering from AD which consumes the most social resources
Summary
Alzheimer’s disease (AD) is a progressive neurodegenerative disease with insidious onset (Peng and Zhao, 2020). The Human Discovery Multi-Analyte Profile (MAP) has become a popular tool to identify plasma analytes These exciting results raise a major issue that it is hard to reproduce these protein panels (Henriksen et al, 2014). Olsson et al (2016) confirmed this view, and they found that the NFL was increasing in both AD patients and MCI’s CSF Studies have found this phenomenon in serum and plasma samples as well (Bacioglu et al, 2016). The main diagnostic methods for Alzheimer’s disease (AD) are positron emission tomography (PET) scanning of the brain and analysis of cerebrospinal fluid (CSF) sample, but these methods are expensive and harmful to patients. Identifying AD-related proteins in blood can help treatment and diagnosis
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