Integrated Bioinformatics Analysis Identifies Hub Genes Associated with Viral Infection and Alzheimer's Disease

A review and analysis of key biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects over 50 million elderly individuals worldwide. Although the pathogenesis of AD is not fully understood, based on current research, researchers are able to identify potential biomarker genes and proteins that may serve as effective targets against AD. This article aims to present a comprehensive overview of recent advances in AD biomarker identification, with highlights on the use of various algorithms, the exploration of relevant biological processes, and the investigation of shared biomarkers with co-occurring diseases. Additionally, this article includes a statistical analysis of key genes reported in the research literature, and identifies the intersection with AD-related gene sets from databases such as AlzGen, GeneCard, and DisGeNet. For these gene sets, besides enrichment analysis, protein-protein interaction (PPI) networks utilized to identify central genes among the overlapping genes. Enrichment analysis, protein interaction network analysis, and tissue-specific connectedness analysis based on GTEx database performed on multiple groups of overlapping genes. Our work has laid the foundation for a better understanding of the molecular mechanisms of AD and more accurate identification of key AD markers.

Systematical analyses of large-scale transcriptome reveal viral infection-related genes and disease comorbidities

Perturbation of transcriptome in viral infection patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent transcriptome and identification of robust biomarkers is not complete. In this study, we manually collected 23 datasets related to 6,197 blood transcriptomes across 16 types of respiratory virus infections. We applied a comprehensive systems biology approach starting with whole-blood transcriptomes combined with multilevel bioinformatics analyses to characterize the expression, functional pathways, and protein-protein interaction (PPI) networks to identify robust biomarkers and disease comorbidities. Robust gene markers of infection with different viruses were identified, which can accurately classify the normal and infected patients in train and validation cohorts. The biological processes (BP) of different viruses showed great similarity and enriched in infection and immune response pathways. Network-based analyses revealed that a variety of viral infections were associated with nervous system diseases, neoplasms and metabolic diseases, and significantly correlated with brain tissues. In summary, our manually collected transcriptomes and comprehensive analyses reveal key molecular markers and disease comorbidities in the process of viral infection, which could provide a valuable theoretical basis for the prevention of subsequent public health events for respiratory virus infections.

Recapitulation of pathophysiological features of AD in SARS-CoV-2-infected subjects

Infection with the etiological agent of COVID-19, SARS-CoV-2, appears capable of impacting cognition in some patients with post-acute sequelae of SARS-CoV-2 (PASC). To evaluate neuropathophysiological consequences of SARS-CoV-2 infection, we examine transcriptional and cellular signatures in the Brodmann area 9 (BA9) of the frontal cortex and the hippocampal formation (HF) in SARS-CoV-2, Alzheimer's disease (AD), and SARS-CoV-2-infected AD individuals compared to age- and gender-matched neurological cases. Here, we show similar alterations of neuroinflammation and blood-brain barrier integrity in SARS-CoV-2, AD, and SARS-CoV-2-infected AD individuals. Distribution of microglial changes reflected by the increase in Iba-1 reveals nodular morphological alterations in SARS-CoV-2-infected AD individuals. Similarly, HIF-1α is significantly upregulated in the context of SARS-CoV-2 infection in the same brain regions regardless of AD status. The finding may help in informing decision-making regarding therapeutic treatments in patients with neuro-PASC, especially those at increased risk of developing AD.

TNIP2 inhibits amyloidogenesis by regulating the 3'UTR of BACE1: an in vitro study

TNFAIP3-interacting protein 2 (TNIP2) is known as a negative regulator of NF-κB signaling and inhibit inflammatory response and apoptosis, and is also involved in RNA metabolism. In this study, we investigated the potential role of TNIP2 in amyloidogenesis critically associated with Alzheimer's disease (AD). We found a significant decline of TNIP2 protein level in both mouse and cell model of AD. In SH-SY5Y and HEK cells that stably express human full-length APP695 (SY5Y-APP and HEK-APP), TNIP2 overexpression decreased the protein levels of β-secretase (BACE1) and C99, as well as Aβ peptides (including Aβ40 and Aβ42), while those of α-secretase (ADAM10) and the related C83 remained unchanged. We further found that TNIP2 promoted the degradation of BACE1 mRNA and was able to bound to the 3' untranslated region (3'UTR) with the reduced luciferase activity. These results indicated that TNIP2 effectively inhibited amyloidogenic processing by regulating the 3'UTR-associated mRNA decay of BACE1.

Molecular and cellular similarities in the brain of SARS-CoV-2 and Alzheimer's disease individuals

Infection with the etiological agent of COVID-19, SARS-CoV-2, appears capable of impacting cognition, which some patients with Post-acute Sequelae of SARS-CoV-2 (PASC). To evaluate neuro-pathophysiological consequences of SARS-CoV-2 infection, we examine transcriptional and cellular signatures in the Broadman area 9 (BA9) of the frontal cortex and the hippocampal formation (HF) in SARS-CoV-2, Alzheimer's disease (AD) and SARS-CoV-2 infected AD individuals, compared to age- and gender-matched neurological cases. Here we show similar alterations of neuroinflammation and blood-brain barrier integrity in SARS-CoV-2, AD, and SARS-CoV-2 infected AD individuals. Distribution of microglial changes reflected by the increase of Iba-1 reveal nodular morphological alterations in SARS-CoV-2 infected AD individuals. Similarly, HIF-1α is significantly upregulated in the context of SARS-CoV-2 infection in the same brain regions regardless of AD status. The finding may help to inform decision-making regarding therapeutic treatments in patients with neuro-PASC, especially those at increased risk of developing AD.

TEASER

SARS-CoV-2 and Alzheimer's disease share similar neuroinflammatory processes, which may help explain neuro-PASC.

Landscape of immune infiltration in entorhinal cortex of patients with Alzheimerʼs disease

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases and manifests as progressive memory loss and cognitive dysfunction. Neuroinflammation plays an important role in the development of Alzheimer’s disease and anti-inflammatory drugs reduce the risk of the disease. However, the immune microenvironment in the brains of patients with Alzheimer’s disease remains unclear, and the mechanisms by which anti-inflammatory drugs improve Alzheimer’s disease have not been clearly elucidated. This study aimed to provide an overview of the immune cell composition in the entorhinal cortex of patients with Alzheimer’s disease based on the transcriptomes and signature genes of different immune cells and to explore potential therapeutic targets based on the relevance of drug targets. Transcriptomics data from the entorhinal cortex tissue, derived from GSE118553, were used to support our study. We compared the immune-related differentially expressed genes (irDEGs) between patients and controls by using the limma R package. The difference in immune cell composition between patients and controls was detected via the xCell algorithm based on the marker genes in immune cells. The correlation between marker genes and immune cells and the interaction between genes and drug targets were evaluated to explore potential therapeutic target genes and drugs. There were 81 irDEGs between patients and controls that participated in several immune-related pathways. xCell analysis showed that most lymphocyte scores decreased in Alzheimer’s disease, including CD4⁺ Tc, CD4⁺ Te, Th1, natural killer (NK), natural killer T (NKT), pro-B cells, eosinophils, and regulatory T cells, except for Th2 cells. In contrast, most myeloid cell scores increased in patients, except in dendritic cells. They included basophils, mast cells, plasma cells, and macrophages. Correlation analysis suggested that 37 genes were associated with these cells involved in innate immunity, of which eight genes were drug targets. Taken together, these results delineate the profile of the immune components of the entorhinal cortex in Alzheimer’s diseases, providing a new perspective on the development and treatment of Alzheimer’s disease.