scholarly journals Clustering Alzheimer’s Disease Gene Expression Dataset Reveals Underlying Sexually Dimorphic and Disease Status Profiles

Author(s):  
Sigal Levy ◽  
Nili Guttmann-Beck ◽  
Dorit Shweiki

Background: The multiple appearance phenotypes in Alzheimer’s disease (AD) are manifested in epidemiologic sexual dimorphism, variation in age of onset, progress, and severity of the disease. Objective: In this study, we focused on sexual dimorphism, aiming to untie some of the complex interconnections in AD between sex, disease status, and gene expression profiles. Two strategic decisions guided our study: 1) to value transcriptomic multi-layered profiles over alterations in single genes expression; and 2) to embrace a sexual dimorphism centered approach, as we suspect that transcriptomic profiles may dramatically differ not only between healthy and sick individuals but between men and women as well. Methods: Microarray dataset GSE15222, fulfilling our strict criteria, was retrieved from the GEO repository. We performed cluster analysis for each sex separately, comparing the proportion of healthy and AD individuals in each cluster. Results: We were able to identify a biased, female, AD-typified cluster. Furthermore, we showed that this female AD-typified cluster is highly similar to one of the male clusters. While the female cluster constitutes mostly sick individuals, the male cluster constitutes healthy and sick individuals in almost identical proportion. Conclusion: Our results clearly indicate that similar transcriptomic profiles in the two sexes are “physiologically translated” in to a very different, dramatic outcome. Thus, our results suggest the need for a sex-based and transcriptomic profile-based study, for a better understanding of the onset and progression of AD.

2007 ◽  
Vol 1127 ◽  
pp. 127-135 ◽  
Author(s):  
Wendy M. Brooks ◽  
Patrick J. Lynch ◽  
Catherine C. Ingle ◽  
Alexander Hatton ◽  
Piers C. Emson ◽  
...  

2014 ◽  
Vol 29 (6) ◽  
pp. 526-532 ◽  
Author(s):  
Bingqian Ding ◽  
Yan Xi ◽  
Ming Gao ◽  
Zhenjiang Li ◽  
Chenyang Xu ◽  
...  

2019 ◽  
Vol 84 ◽  
pp. 98-108 ◽  
Author(s):  
Elaheh Moradi ◽  
Mikael Marttinen ◽  
Tomi Häkkinen ◽  
Mikko Hiltunen ◽  
Matti Nykter

2020 ◽  
Author(s):  
Shahan Mamoor

We sought to understand, at the systems level and in an unbiased fashion, how gene expression was most different in the brains of patients with Alzheimer’s Disease (AD) by mining published microarray datasets (1, 2). Comparing global gene expression profiles between patient and control revealed that a set of 84 genes were expressed at significantly different levels in the middle temporal gyrus (MTG) of patients with Alzheimer’s Disease (1, 2). We used computational analyses to classify these genes into known pathways and existing gene sets, and to describe the major differences in the epigenetic marks at the genomic loci of these genes. While a portion of these genes is computationally cognizable as part of a set of genes up-regulated in the brains of patients with AD (3), many other genes in the gene set identified here have not previously been studied in association with AD. Transcriptional repression, both pre- and post-transcription appears to be affected; nearly 40% of these genes are transcriptional targets of MicroRNA-19A/B (miR-19A/B), the zinc finger protein 10 (ZNF10), or of the AP-1 repressor jun dimerization protein 2 (JDP2).


2016 ◽  
Vol 22 (2) ◽  
pp. 296-305 ◽  
Author(s):  
A C Pereira ◽  
J D Gray ◽  
J F Kogan ◽  
R L Davidson ◽  
T G Rubin ◽  
...  

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