Global Gene Expression Profiling and Transcription Factor Network Analysis of Cognitive Aging in Monozygotic Twins - Mohammadnejad, Afsaneh; Li, Weilong; Lund, Jesper Beltoft; Li, Shuxia; Larsen, Martin J.; Mengel-From, Jonas; Michel, Tanja Maria; Christiansen, Lene; Christensen, Kaare; Hjelmborg, Jacob; Baumbach, Jan; Tan, Qihua (Frontiers in Genetics, 2021)
Cognitive Aging is one of the major problems worldwide, especially as people get older. This study aimed to perform a global gene expression profiling of cognitive function to identify associated genes and pathways and a novel transcriptional regulatory network analysis to identify important regulons. We performed single transcript analysis on 400 monozygotic twins using an assumption-free generalized correlation coefficient (GCC), linear mixed-effect model (LME) and kinship model and identified 6 probes (one significant at the standard FDR < 0.05 while the other results were suggestive with 0.18 ≤ FDR ≤ 0.28). We combined GCC and linear models' results to cover diverse patterns of relationships and meaningful and novel genes like APOBEC3G, H6PD, SLC45A1, GRIN3B and PDE4D were detected. Our exploratory study showed the downregulation of all these genes with increasing cognitive function or vice versa except SLC45A1 gene, which upregulated with increasing cognitive function. Linear models found only H6PD and SLC45A1, the other genes were captured by GCC. Significant functional pathways (FDR < 3.95 e-10) such as focal adhesion, ribosome, cysteine and methionine metabolism, Huntington's disease, eukaryotic translation elongation, nervous system development, influenza infection, metabolism of RNA and cell cycle were identified. A total of 5 regulons (FDR< 1.3e-4) were enriched in a transcriptional regulatory analysis in which CTCF and REST were activated and SP3, SRF, and XBP1 were repressed regulons. The genome-wide transcription analysis using both assumption-free GCC and linear models identified important genes and biological pathways implicated in cognitive performance, cognitive aging, and neurological diseases. Also, the regulatory network analysis revealed significant activated and repressed regulons on cognitive function.