Cross-disease analysis of Alzheimer\u2019s disease and type-2 Diabetes highlights the role of autophagy in the pathophysiology of two highly comorbid diseases

Laura Caberlotto,Angel Cedazo-Minguez,Mauro Corsi,Roberto Rimondini,Silvia Maioli,T.-Phuong Nguyen,Corrado Priami,Mario Lauria,Giulia Sita,Lucia Carboni,Fabiana Morroni

doi:10.1038/s41598-019-39828-5

Abstract

Evidence is accumulating that the main chronic diseases of aging Alzheimer’s disease (AD) and type-2 diabetes mellitus (T2DM) share common pathophysiological mechanisms. This study aimed at applying systems biology approaches to increase the knowledge of the shared molecular pathways underpinnings of AD and T2DM. We analysed transcriptomic data of post-mortem AD and T2DM human brains to obtain disease signatures of AD and T2DM and combined them with protein-protein interaction information to construct two disease-specific networks. The overlapping AD/T2DM network proteins were then used to extract the most representative Gene Ontology biological process terms. The expression of genes identified as relevant was studied in two AD models, 3xTg-AD and ApoE3/ApoE4 targeted replacement mice. The present transcriptomic data analysis revealed a principal role for autophagy in the molecular basis of both AD and T2DM. Our experimental validation in mouse AD models confirmed the role of autophagy-related genes. Among modulated genes, Cyclin-Dependent Kinase Inhibitor 1B, Autophagy Related 16-Like 2, and insulin were highlighted. In conclusion, the present investigation revealed autophagy as the central dys-regulated pathway in highly co-morbid diseases such as AD and T2DM allowing the identification of specific genes potentially involved in disease pathophysiology which could become novel targets for therapeutic intervention.

Highlights

While the cause of Alzheimer’s disease (AD) remains unknown, several risk factors have been identified that may provide insight into the fundamentals of AD pathogenesis
Having obtained four well defined groups representing all combinations of our two phenotypes of interest (T2DM and AD), we sought to characterize them transcriptionally in a highly specific way, in the sense of identifying genes whose expression changes were most related to a single phenotype
We found that it was necessary to perform a preliminary feature selection step in order to preferentially steer the algorithm toward brain transcriptional alterations that have some association to type-2 diabetes mellitus (T2DM) and AD, reducing the influence of other factors such age, sex, tissue of origin

Summary

Introduction

While the cause of AD remains unknown, several risk factors have been identified that may provide insight into the fundamentals of AD pathogenesis. A novel approach to the analysis of existing transcriptional data-sets of T2DM and AD patient cerebral cortex material was used, with a major application to human brain networks (Fig. 1) This integration of knowledge highlighted a central role for the autophagy pathway in the mechanisms underlying the commonalities in AD and T2DM, which was further analyzed in animal models of disease. We focus our investigation initially on human diseased subjects considering the limitation of animal models of CNS-related diseases in representing all aspects of a complex multifactorial disease, but we were able to confirm and investigate further the molecular mechanism found to be altered in two models that represent different aspects of the genetic of AD These findings contribute to opening new ways to tackle some of the more important challenges to combat these disorders

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