A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer’s disease progression

Ray et al. BMC Bioinformatics (2017) 18:579 DOI 10.1186/s12859-017-1946-8 METHODOLOGY ARTICLE Open Access A comprehensive analysis on preservation patterns of gene co-expression networks during Alzheimer’s disease progression Sumanta Ray1† , Sk Md Mosaddek Hossain1*† , Lutfunnesa Khatun1 and Anirban Mukhopadhyay2 Abstract Background: Alzheimer’s disease (AD) is a chronic neuro-degenerative disruption of the brain which involves in large scale transcriptomic variation. The disease does not impact every regions of the brain at the same time, instead it progresses slowly involving somewhat sequential interaction with different regions. Analysis of the expression patterns of the genes in different regions of the brain influenced in AD surely contribute for a enhanced comprehension of AD pathogenesis and shed light on the early characterization of the disease. Results: Here, we have proposed a framework to identify perturbation and preservation characteristics of gene expression patterns across six distinct regions of the brain (“EC”, “HIP”, “PC”, “MTG”, “SFG”, and “VCX”) affected in AD. Co-expression modules were discovered considering a couple of regions at once. These are then analyzed to know the preservation and perturbation characteristics. Different module preservation statistics and a rank aggregation mechanism have been adopted to detect the changes of expression patterns across brain regions. Gene ontology (GO) and pathway based analysis were also carried out to know the biological meaning of preserved and perturbed modules. Conclusions: In this article, we have extensively studied the preservation patterns of co-expressed modules in six distinct brain regions affected in AD. Some modules are emerged as the most preserved while some others are detected as perturbed between a pair of brain regions. Further investigation on the topological properties of preserved and non-preserved modules reveals a substantial association amongst “betweenness centrality” and ”degree” of the involved genes. Our findings may render a deeper realization of the preservation characteristics of gene expression patterns in discrete brain regions affected by AD. Keywords: Module preservation measures, Gene co-expression networks, Hierarchical clustering, Rank aggregation Background Alzheimer’s disease (AD) has been characterized as an irreversible, progressive neuro-degenerative incoherence in the brain and the major reason of dementia [1]. In AD, connections between cells in the brain are destroyed and eventually these cells die, which affects how the brain works. On its early onset, it is classified as short-term loss of memory. As the disease progresses, people suffers from issues with dialect, disorientation (letting in easily getting *Correspondence: † Equal contributors 1 Department of Computer Science and Engineering, Aliah University, West Bengal, 700156 Kolkata, India Full list of author information is available at the end of the article lost), loss of inspiration, mood swings, behavioral problems, not accomplishing self-care, and thus they are often kept isolated from family and the society. Its progression can be summarized in three stages: Early (“mild”), Middle (“moderate”) and Late (“severe”) [1, 2]. Typically, Alzheimer’s disease starts with very insignificant effects on the individuals capabilities or behavior. Initially it is characterized by memory loss, especially memory of more recent events which more often mistakenly classified as issues due to stress or mourning or in elderly persons, as the ordinary consequence of ageing (“mild stage”). As the disease advances (“moderate stage”), patient’s professional and social functioning continues to deteriorate because of increasing problems with © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Ray et al. BMC Bioinformatics (2017) 18:579 memory, logic, speech, and initiative and the affected individual become incapable of performing natural activities of every day living [3]. In this stage, the most regions of the brain undergo severe impairment and drastically shrinks because of extensive cell death. During the final (“severe”) stage, patients become completely dependent upon caregivers [3, 4] and their dialect is lessened to basic expressions or many a time single words, finally prompting complete loss of discourse. There are certain brain regions which are more susceptible to AD than others in terms of pathological and metabolic characteristics, although it does not affect all brain regions simultaneously [5–9]. It begins in the “entorhinal cortex” (EC) and “hippocampus” (HIP) [10]. Other brain regions such as the “middle temporal gyrus” (MTG) and the “posterior cingulate cortex” (PC) get affected later during progression of the disease [10, 11]. Thus, it is more significant to know the co-expression changes during the progression of AD from EC or HIP region to other brain regions. Dr. Alois Alzheimer characterized the symptoms of the disease in 1906. But the genesis of AD has continued to be elusive since then. Merely the “APOE” gene was observed to be related to AD in 1993. Thereafter, numerous analysis have been carried out to detect the genes which are expressed differentially in the Alzheimer’s disease influenced brain regions [12, 13]. In [14] Ray et al. differentiated 18-protein signatures in peripheral blood plasma which can be utilized to forecast the clinical syndromes of AD in advance well before the symptoms are apparent. Liang et al. [5] carried out a comprehensive analysis and discovered that “APOE”, “BACE1”, “FYN”, “GGA1”, “SORL1” and “STUB1 (CHIP)” genes are expressed differentially in postmortem gene expression dataset of six distinct brain regions. Moreover, they have indicated the genes which observed substantial changes in their expression patterns due to AD. Ray et al. [13] analyzed microarray data across four discrete brain regions (EC, HIP, PC, MTG) by constructing gene co-expression network for each region using differentially expressed genes amongst AD affected and normal control samples. They have identified the genes associated with “zero topological overlap” between a pair of regions specific networks to characterize the differences between the two brain regions. A network-based systems biology methodology was proposed to analyze the Alzheimer’s disease associated pathways and their disfunctions among six discrete brain regions by Liu e (...truncated)