Endocytosis-pathway polygenic scores affects the hippocampal network connectivity and individualized identification across the high-risk of Alzheimer's disease

Exploring the common pathogenesis of Alzheimer's disease and type 2 diabetes mellitus via microarray data analysis

Background

Alzheimer's Disease (AD) and Type 2 Diabetes Mellitus (DM) have an increased incidence in modern society. Although more and more evidence has supported that DM is prone to AD, the interrelational mechanisms remain fully elucidated.

Purpose

The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and DM.

Methods

Download the expression matrix of AD and DM from the Gene Expression Omnibus (GEO) database with sequence numbers GSE97760 and GSE95849, respectively. The common differentially expressed genes (DEGs) were identified by limma package analysis. Then we analyzed the six kinds of module analysis: gene functional annotation, protein-protein interaction (PPI) network, potential drug screening, immune cell infiltration, hub genes identification and validation, and prediction of transcription factors (TFs).

Results

The subsequent analyses included 339 common DEGs, and the importance of immunity, hormone, cytokines, neurotransmitters, and insulin in these diseases was underscored by functional analysis. In addition, serotonergic synapse, ovarian steroidogenesis, estrogen signaling pathway, and regulation of lipolysis are closely related to both. DEGs were input into the CMap database to screen small molecule compounds with the potential to reverse AD and DM pathological functions. L-690488, exemestane, and BMS-345541 ranked top three among the screened small molecule compounds. Finally, 10 essential hub genes were identified using cytoHubba, including PTGS2, RAB10, LRRK2, SOS1, EEA1, NF1, RAB14, ADCY5, RAPGEF3, and PRKACG. For the characteristic Aβ and Tau pathology of AD, RAPGEF3 was associated significantly positively with AD and NF1 significantly negatively with AD. In addition, we also found ADCY5 and NF1 significant correlations with DM phenotypes. Other datasets verified that NF1, RAB14, ADCY5, and RAPGEF3 could be used as key markers of DM complicated with AD. Meanwhile, the immune cell infiltration score reflects the different cellular immune microenvironments of the two diseases.

Conclusion

The common pathogenesis of AD and DM was revealed in our research. These common pathways and hub genes directions for further exploration of the pathogenesis or treatment of these two diseases.

Functional Integrity of Executive Control Network Contributed to Retained Executive Abilities in Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is considered to be a transitional state between normal aging and Alzheimer's dementia (AD). Recent studies have indicated that executive function (EF) declines during MCI. However, only a limited number of studies have investigated the neural basis of EF deficits in MCI. Herein, we investigate the changes of regional brain spontaneous activity and functional connectivity (FC) of the executive control network (ECN) between high EF and low EF groups. Methods: According to EF composite score (ADNI-EF) from the Alzheimer's Disease Neuroimaging Initiative (ADNI), we divided MCI into two groups, including the MCI-highEF group and MCI-lowEF group. Resting-state functional MRI was utilized to investigate the fractional amplitude of low-frequency fluctuation (fALFF) and ECN functional connectivity across 23 healthy controls (HC), 11 MCI-highEF, and 14 MCI-lowEF participants. Moreover, a partial correlation analysis was carried out to examine the relationship between altered fALFF or connectivity of the ECN and the ADNI-EF. Results: Compared to HC, the MCI-highEF participants demonstrated increased fALFF in the left superior temporal gyrus (STG), as well as decreased fALFF in the right precentral gyrus, right postcentral gyrus, and left middle frontal gyrus (MFG). The MCI-lowEF participants demonstrated increased fALFF in the cerebellar vermis and decreased fALFF in the left MFG. Additionally, compared to HC, the MCI-highEF participants indicated no significant difference in connectivity of the ECN. Furthermore, the MCI-lowEF participants showed increased ECN FC in the left cuneus and left MFG, as well as decreased ECN functional connectivity in the right parahippocampal gyrus (PHG). Notably, the altered fALFF in the left MFG was positively correlated to ADNI-EF, while the altered fALFF in cerebellar vermis is negatively correlated with ADNI-EF across the two MCI groups and the HC group. Altered ECN functional connectivity in the right PHG is negatively correlated to ADNI-EF, while altered ECN functional connectivity in the left cuneus is negatively correlated to ADNI-EF across the three groups. Conclusions: Our current study demonstrates the presence of different patterns of regional brain spontaneous activity and ECN FC in the MCI-highEF group and MCI-lowEF group. Furthermore, the ECN FC of the MCI-highEF group was not disrupted, which may contribute to retained EF in MCI.

Global Gene Expression Profiling and Transcription Factor Network Analysis of Cognitive Aging in Monozygotic Twins

Cognitive aging is one of the major problems worldwide, especially as people get older. This study aimed to perform 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 six probes (one significant at the standard FDR < 0.05 while the other results were suggestive with 0.18 ≤ FDR ≤ 0.28). We combined the GCC and linear model 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 the SLC45A1 gene, which was upregulated with increasing cognitive function. Linear models found only H6PD and SLC45A1, the other genes were captured by GCC. Significant functional pathways (FDR < 3.95e-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 five 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.