Integrated analysis of ischemic stroke datasets revealed sex and age difference in anti-stroke targets

Abstract

Ischemic stroke is a common neurological disorder and the burden in the world is growing. This study aims to explore the effect of sex and age difference on ischemic stroke using integrated microarray datasets. The results showed a dramatic difference in whole gene expression profiles and influenced pathways between males and females, and also in the old and young individuals. Furthermore, compared with old males, old female patients showed more serious biological function damage. However, females showed less affected pathways than males in young subjects. Functional interaction networks showed these differential expression genes were mostly related to immune and inflammation-related functions. In addition, we found ARG1 and MMP9 were up-regulated in total and all subgroups. Importantly, IL1A, ILAB, IL6 and TNF and other anti-stroke target genes were up-regulated in males. However, these anti-stroke target genes showed low expression in females. This study found huge sex and age differences in ischemic stroke especially the opposite expression of anti-stroke target genes. Future studies are needed to uncover these pathological mechanisms, and to take appropriate pre-prevention, treatment and rehabilitation measures.

Integrative machine learning analysis of multiple gene expression profiles in cervical cancer

“…Despite the many approaches which were introduced in the previous meta-analysis study, a biased issue that is caused by merging datasets from different platforms and experiments is a hot topic in the field. Alles et al (2009) , Chow, Alias & Jamal (2017) , Dong et al (2010) and Li et al (2016) carried out meta-analysis in various type of cancers to find the significant genes in certain diseases such as breast cancer, paediatric B-acute lymphoblastic leukaemia (B-ALL), ovarian cancer, etc. Trendily, most of these studies were done by using the original datasets that varied from different platforms.…”

“…Furthermore, until the present, most of the previous studies either used statistical analysis methods ( Alles et al, 2009 ; Chow, Alias & Jamal, 2017 ; Dong et al, 2010 ; Li et al, 2016 ) or machine learning-based methods ( Chow, Alias & Jamal, 2017 ; Dong et al, 2010 ; Li et al, 2016 ; Grützmann et al, 2005 ; Liu et al, 2004 ; Obayashi & Kinoshita, 2009 ; Wang & Makedon, 2004 ; Díaz-Uriarte & De Andres, 2006 ) in carrying out the meta-analysis. Due to different measurements being used in analysing the expression activities in the genes, there is no way in comparing the feasibility of both methods in a meta-analysis.…”

Interleukin–6 ( IL-6 ) rs1800796 and cyclin dependent kinase inhibitor ( CDKN2A/CDKN2B ) rs2383207 are associated with ischemic stroke in indigenous West African Men

“…(2015) using integrated microarray datasets, in which IL-6 gene expression was significantly upregulated in male patients but down – regulated in female patients. 28 This evidence provides a possible genetic basis for gender disparity in the epidemiology of stroke 5,15,16,29,30 .…”

Low expression of aging-related NRXN3 is associated with Alzheimer disease

“…[ 14 ] Gene annotation and integration of the AD datasets were performed using a custom written Python code. [ 15 ] The 3 AD datasets were further analyzed using metaMA, which applied the empirical Bayes moderated t -statistic and weighted meta-analysis to calculate DEGs in each dataset, and then adjusted the P values with a false discovery rate (FDR). [ 16 ] As a result, a Z score was assigned to each DEG, as per previous research.…”