Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease

Identification of genetic biomarkers associated with pharmacokinetics and pharmacodynamics of apixaban in Chinese healthy volunteers

BACKGROUND

Apixaban is a superior direct oral anticoagulant exihibiting interindividual variability in concentration and response in the real world. The present study aimed to identify genetic biomarkers associated with pharmacokinetics (PK) and pharmacodynamics (PD) of apixaban in healthy Chinese subjects.

METHODS

This multicenter study included 181 healthy Chinese adults taking a single dose of 2.5 mg or 5 mg apixaban and assessed their PK and PD parameters. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed using the Affymetrix Axiom CBC_PMRA Array. Candidate gene association analysis and genome-wide association study were conducted to identify genes with a predictive value for PK and PD parameters of apixaban.

RESULTS

Several ABCG2 variants were associated with C_max and AUC_0-t of apixaban (p < 6.12 × 10^-5) and also presented significant differences of anti-Xa_3h activity and dPT_3h according to different ABCG2 genotypes (p < 0.05). Besides, ABLIM2 variants were found to be associated with PK characteristics and F13A1 and C3 variants were associated with PD characteristics of apixaban (p < 9.46 × 10^-8).

CONCLUSION

ABCG2 variants were found to be ideal genetic biomarkers for both PK and PD characteristics of apixaban. ABLIM2, F13A1 and C3 were identified as potential candidate genes associated with inter-individual variability of apixaban. This study was registered on ClinicalTrials.gov NCT03259399.

A review of brain imaging biomarker genomics in Alzheimer’s disease: implementation and perspectives

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with phenotypic changes closely associated with both genetic variants and imaging pathology. Brain imaging biomarker genomics has been developed in recent years to reveal potential AD pathological mechanisms and provide early diagnoses. This technique integrates multimodal imaging phenotypes with genetic data in a noninvasive and high-throughput manner. In this review, we summarize the basic analytical framework of brain imaging biomarker genomics and elucidate two main implementation scenarios of this technique in AD studies: (1) exploring novel biomarkers and seeking mutual interpretability and (2) providing a diagnosis and prognosis for AD with combined use of machine learning methods and brain imaging biomarker genomics. Importantly, we highlight the necessity of brain imaging biomarker genomics, discuss the strengths and limitations of current methods, and propose directions for development of this research field.

Effect of Resveratrol Combined with Donepezil Hydrochloride on Inflammatory Factor Level and Cognitive Function Level of Patients with Alzheimer's Disease

Objective

To explore the effect of resveratrol (RES) combined with donepezil hydrochloride on inflammatory factor level and cognitive function level of patients with Alzheimer's disease (AD).

Methods

A total of 90 AD patients treated in our hospital from June 2019 to June 2020 were selected as the study objects and divided into the control group (CG) and experimental group (EG) by the randomized and double-blind method, with 45 cases each. Patients in CG received donepezil hydrochloride treatment, and on this basis, those in EG received additional RES treatment, so as to compare the clinical indicators between the two groups.

Results

Compared with CG after treatment, EG obtained significantly higher good rate, MMSE score, and FIM score (P < 0.05) and obviously lower clinical indicators and ADAS-cog score (P < 0.001), and between CG and EG, no obvious difference in total incidence rate of adverse reactions was observed after treatment (P > 0.05).

Conclusion

Combining RES with donepezil hydrochloride has significant clinical efficacy in treating AD, which can effectively improve patients' inflammatory factor indicators, promote their cognitive function, and facilitate patient prognosis.

Identification and Validation of a Dysregulated miRNA-Associated mRNA Network in Temporal Lobe Epilepsy

Objectives

This study is aimed at exploring the relationships between miRNAs and mRNAs and to characterize their biological functions in temporal lobe epilepsy (TLE).

Methods

Novel clinical significant miRNAs and target genes and their potential underlying mechanisms have been discovered and explored by mining miRNAs and mRNA expression data of TLE patients using various bioinformatics methods. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used to validate the bioinformatic analysis results.

Results

A total of 6 dysregulated miRNAs and 442 differentially expressed genes (DEGs) related to TLE were obtained from GEO database (GSE114701 and GSE127871 datasets). A protein-protein interaction (PPI) network containing the 442 DEGs was established. mRNA response elements from the 6 dysregulated miRNAs were predicted using the miRDB and TargetScan bioinformatic tools. By merging the identified targets of the dysregulated miRNAs and the 247 downregulated DEGs, a miRNA-mRNA network was constructed revealing the interaction of miR-484 with eight mRNAs (ABLIM2, CEP170B, CTD-3193O13.9, EFNA5, GAP43, PRKCB, FXYD7, and NCAN). A weighted correlation network analysis (WGCNA) based on the eight genes was established and demonstrated that these mRNAs, except FXYD7 and NCAN, were hub genes in the network. Gene Oncology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis revealed that the six hub genes were mainly involved in cellular-related biological functions and the neurotransmitter synapse pathway. The differences in expression levels of the miR-484 and the three hub genes (CTD-3193O13.9, EFNA5, and PRKCB) observed experimentally in TLE patients compared to those of healthy controls were consistent with the WGCNA prediction.

Conclusion

Our study suggests that understanding the miRNA-mRNA interactions will provide insights into the epilepsy pathogenesis. In addition, our results indicate that miR-484 may be a promising novel biomarker for TLE.

Dimethylarginine dimethylaminohydrolase 1 as a novel regulator of oligodendrocyte differentiation in the central nervous system remyelination

Remyelination is a regenerative process that restores the lost neurological function and partially depends on oligodendrocyte differentiation. Differentiation of oligodendrocytes spontaneously occurs after demyelination, depending on the cell intrinsic mechanisms. By combining a loss-of-function genomic screen with a web-resource-based candidate gene identification approach, we identified that dimethylarginine dimethylaminohydrolase 1 (DDAH1) is a novel regulator of oligodendrocyte differentiation. Silencing DDAH1 in oligodendrocytes prevented the expression of myelin basic protein in mouse oligodendrocyte culture with the change in expression of genes annotated with oligodendrocyte development. DDAH1 inhibition attenuated spontaneous remyelination in a cuprizone-induced demyelinated mouse model. Conversely, increased DDAH1 expression enhanced remyelination capacity in experimental autoimmune encephalomyelitis. These results provide a novel therapeutic option for demyelinating diseases by modulating DDAH1 activity.

Bioinformatics analysis of differentially expressed genes and identification of an miRNA-mRNA network associated with entorhinal cortex and hippocampus in Alzheimer's disease

Background

Alzheimer’s disease (AD) is a fatal neurodegenerative disorder, and the lesions originate in the entorhinal cortex (EC) and hippocampus (HIP) at the early stage of AD progression. Gaining insight into the molecular mechanisms underlying AD is critical for the diagnosis and treatment of this disorder. Recent discoveries have uncovered the essential roles of microRNAs (miRNAs) in aging and have identified the potential of miRNAs serving as biomarkers in AD diagnosis.

Methods

We sought to apply bioinformatics tools to investigate microarray profiles and characterize differentially expressed genes (DEGs) in both EC and HIP and identify specific candidate genes and pathways that might be implicated in AD for further analysis. Furthermore, we considered that DEGs might be dysregulated by miRNAs. Therefore, we investigated patients with AD and healthy controls by studying the gene profiling of their brain and blood samples to identify AD-related DEGs, differentially expressed miRNAs (DEmiRNAs), along with gene ontology (GO) analysis, KEGG pathway analysis, and construction of an AD-specific miRNA–mRNA interaction network.

Results

Our analysis identified 10 key hub genes in the EC and HIP of patients with AD, and these hub genes were focused on energy metabolism, suggesting that metabolic dyshomeostasis contributed to the progression of the early AD pathology. Moreover, after the construction of an miRNA–mRNA network, we identified 9 blood-related DEmiRNAs, which regulated 10 target genes in the KEGG pathway.

Conclusions

Our findings indicated these DEmiRNAs having the potential to act as diagnostic biomarkers at an early stage of AD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-021-00190-0.

Proteomics and transcriptomics jointly identify the key role of oxidative phosphorylation in fluoride-induced myocardial mitochondrial dysfunction in rats

The regulation of mitochondrial function, which is dominated by oxidative phosphorylation (OXPHOs), is important in fluoride induced cardiovascular disease. Based on the previous study of fluoride-induced mitochondrial structure and membrane potential abnormalities, this study integrated ITRAQ protein quantification and RNA-Seq methods to analyze the sequencing data of rat myocardial tissue under fluoride exposure (0, 30, 60 and 90 mg/L). A total of 22 differentially expressed genes associated with the OXPHOs pathway were screened by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) co-enrichment analysis, and were localizated by Interaction Network and calculated inter-genes and inter-omics correlations by Pearson correlation. In general, fluoride exposure can down-regulate genes related OXPHOs, particularly affecting the assembly of the complex I including Ndufa10, resulting in abnormal mitochondrial ATP synthesis and reduced myocardial energy supply. Most importantly, this study shows that the enriched information from the proteomics can explain the change process of energy production, but the specific molecules involved in energy supply cannot be obtained via transcriptomics information alone. Based on the results of transcriptional and protein analysis, our findings contribute to an innovative understanding of the pathways and molecular changes of myocardial injury induced by fluorosis.

Disentangling the Molecular Pathways of Parkinson's Disease using Multiscale Network Modeling

Parkinson's disease (PD) is a complex neurodegenerative disorder. The identification of genetic variants has shed light on the molecular pathways for inherited PD, while the disease mechanism for idiopathic PD remains elusive, partly due to a lack of robust tools. The complexity of PD arises from the heterogeneity of clinical symptoms, pathologies, environmental insults contributing to the disease, and disease comorbidities. Molecular networks have been increasingly used to identify molecular pathways and drug targets in complex human diseases. Here, we review recent advances in molecular network approaches and their application to PD. We discuss how network modeling can predict functions of PD genetic risk factors through network context and assist in the discovery of network-based therapeutics for neurodegenerative diseases.

Multivariate genome wide association and network analysis of subcortical imaging phenotypes in Alzheimer's disease

BACKGROUND

Genome-wide association studies (GWAS) have identified many individual genes associated with brain imaging quantitative traits (QTs) in Alzheimer's disease (AD). However single marker level association discovery may not be able to address the underlying biological interactions with disease mechanism.

RESULTS

In this paper, we used the MGAS (Multivariate Gene-based Association test by extended Simes procedure) tool to perform multivariate GWAS on eight AD-relevant subcortical imaging measures. We conducted multiple iPINBPA (integrative Protein-Interaction-Network-Based Pathway Analysis) network analyses on MGAS findings using protein-protein interaction (PPI) data, and identified five Consensus Modules (CMs) from the PPI network. Functional annotation and network analysis were performed on the identified CMs. The MGAS yielded significant hits within APOE, TOMM40 and APOC1 genes, which were known AD risk factors, as well as a few new genes such as LAMA1, XYLB, HSD17B7P2, and NPEPL1. The identified five CMs were enriched by biological processes related to disorders such as Alzheimer's disease, Legionellosis, Pertussis, and Serotonergic synapse.

CONCLUSIONS

The statistical power of coupling MGAS with iPINBPA was higher than traditional GWAS method, and yielded new findings that were missed by GWAS. This study provides novel insights into the molecular mechanism of Alzheimer's Disease and will be of value to novel gene discovery and functional genomic studies.