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

Alzheimer's disease pathogenetic progression is associated with changes in regulated retained introns and editing of circular RNAs

Introduction

The molecular changes leading to Alzheimer's disease (AD) progression are poorly understood. A decisive factor in the disease occurs when neurofibrillary tangles (NFT) composed of microtubule associated protein tau (MAPT) form in the entorhinal cortex and then spread throughout the brain.

Methods

We therefore determined mRNA and circular RNA changes during AD progression, comparing Braak NFT stages I-VI. Total RNA was isolated from human brain (entorhinal and frontotemporal cortex). Poly(A)+ RNA was subjected to Nanopore sequencing, and total RNA was analyzed by standard Illumina sequencing. Circular RNAs were sequenced from RNase R treated and rRNA depleted total RNA. The sequences were analyzed using different bioinformatic tools, and expression constructs for circRNAs were analyzed in transfection experiments.

Results

We detected 11,873 circRNAs of which 276 correlated with Braak NFT stages. Adenosine to inosine RNA editing increased about threefold in circRNAs during AD progression. Importantly, this correlation cannot be detected with mRNAs. CircMAN2A1 expression correlated with AD progression and transfection experiments indicated that RNA editing promoted its translation using start codons out of frame with linear mRNAs, which generates novel proteins.

Discussion

Thus, we identified novel regulated retained introns that correlate with NFT Braak stages and provide evidence for a role of translated circRNAs in AD development.

Neurodegenerative disorders: From clinicopathology convergence to systems biology divergence

Neurodegenerative diseases are multifactorial. This means that several genetic, epigenetic, and environmental factors contribute to their emergence. Therefore, for the future management of these highly prevalent diseases, it is necessary to change perspective. If a holistic viewpoint is assumed, the phenotype (the clinicopathological convergence) emerges from the perturbation of a complex system of functional interactions among proteins (systems biology divergence). The systems biology top-down approach starts with the unbiased collection of sets of data generated through one or more -omics techniques and has the aim to identify the networks and the components that participate in the generation of a phenotype (disease), often without any available a priori knowledge. The principle behind the top-down method is that the molecular components that respond similarly to experimental perturbations are somehow functionally related. This allows the study of complex and relatively poorly characterized diseases without requiring extensive knowledge of the processes under investigation. In this chapter, the use of a global approach will be applied to the comprehension of neurodegeneration, with a particular focus on the two most prevalent ones, Alzheimer's and Parkinson's diseases. The final purpose is to distinguish disease subtypes (even with similar clinical manifestations) to launch a future of precision medicine for patients with these disorders.

Comprehensive Analysis of Transcriptomic Profiles Identified the Prediction of Prognosis and Drug Sensitivity of Aminopeptidase-Like 1 (NPEPL1) for Clear Cell Renal Cell Carcinoma

Aminopeptidase-like 1 (NPEPL1) is a member of the aminopeptidase group that plays a role in the development and progression of various diseases. Expression of NPEPL1 has been reported to be involved in prostate, breast, and colorectal cancers. However, the role and mechanism of NPEPL1 in clear cell renal cell carcinoma (ccRCC) are unclear. The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases were used to predict the relationship between clinicopathological features and NPEPL1 expression. Changes in immune status and drug sensitivity with NPEPL1 expression were analyzed by the "CIBERSORT" function in R software. The results found that NPEPL1 expression was upregulated in ccRCC tissues, with expression progressively increasing with ccRCC stage and grade. Patients with high NPEPL1 expression presented with a poor prognosis across different clinicopathological features. Univariate and multivariate Cox regression analyses indicated that aberrant NPEPL1 expression was an independent risk factor for ccRCC. The nomogram showed that NPEPL1 expression improved the accuracy of predicting the prognosis of ccRCC patients. The Gene Ontology (GO) term enrichment analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that NPEPL1 may be involved in the development of ccRCC through the voltage-gated calcium channel complex, channel activity, cAMP signaling pathway, and oxytocin signaling pathway. The coexpression analysis found that NPEPL1 altered tumor characteristics by interacting with related genes. The "CIBERSORT" analysis showed that elevated NPEPL1 expression was followed by an enrichment of regulatory T cells and follicular helper T cells in the microenvironment. The drug sensitivity analysis found patients with high NPEPL1 expression had a higher benefit from axitinib, cisplatin, and GSK429286A. In conclusion, upregulation of NPEPL1 expression was involved in ccRCC prognosis and treatment. NPEPL1 could be used as a therapeutic target to guide clinical dosing.

Determinants of approved acetylcholinesterase inhibitor response outcomes in Alzheimer's disease: relevance for precision medicine in neurodegenerative diseases

Acetylcholinesterase inhibitors (ChEI) are the global standard of care for the symptomatic treatment of Alzheimer's disease (AD) and show significant positive effects in neurodegenerative diseases with cognitive and behavioral symptoms. Although experimental and large-scale clinical evidence indicates the potential long-term efficacy of ChEI, primary outcomes are generally heterogeneous across outpatient clinics and regional healthcare systems. Sub-optimal dosing or slow tapering, heterogeneous guidelines about the timing for therapy initiation (prodromal versus dementia stages), healthcare providers' ambivalence to treatment, lack of disease awareness, delayed medical consultation, prescription of ChEI in non-AD cognitive disorders, contribute to the negative outcomes. We present an evidence-based overview of determinants, spanning genetic, molecular, and large-scale networks, involved in the response to ChEI in patients with AD and other neurodegenerative diseases. A comprehensive understanding of cerebral and retinal cholinergic system dysfunctions along with ChEI response predictors in AD is crucial since disease-modifying therapies will frequently be prescribed in combination with ChEI. Therapeutic algorithms tailored to genetic, biological, clinical (endo)phenotypes, and disease stages will help leverage inter-drug synergy and attain optimal combined response outcomes, in line with the precision medicine model.

Advances in Genetics and Epigenetic Alterations in Alzheimer's Disease: A Notion for Therapeutic Treatment

Alzheimer's disease (AD) is a disabling neurodegenerative disorder that leads to long-term functional and cognitive impairment and greatly reduces life expectancy. Early genetic studies focused on tracking variations in genome-wide DNA sequences discovered several polymorphisms and novel susceptibility genes associated with AD. However, despite the numerous risk factors already identified, there is still no fully satisfactory explanation for the mechanisms underlying the onset of the disease. Also, as with other complex human diseases, the causes of low heritability are unclear. Epigenetic mechanisms, in which changes in gene expression do not depend on changes in genotype, have attracted considerable attention in recent years and are key to understanding the processes that influence age-related changes and various neurological diseases. With the recent use of massive sequencing techniques, methods for studying epigenome variations in AD have also evolved tremendously, allowing the discovery of differentially expressed disease traits under different conditions and experimental settings. This is important for understanding disease development and for unlocking new potential AD therapies. In this work, we outline the genomic and epigenomic components involved in the initiation and development of AD and identify potentially effective therapeutic targets for disease control.

Biologia Futura: progress and future perspectives of long non-coding RNAs in forest trees

Forest trees are affected by climate change, anthropogenic pressure, as well as abiotic and biotic stresses. Conventional tree breeding has so far been limited to enhance overall productivity, and our understanding of the genetic basis of quantitative traits is still inadequate. Quantum leaps in next-generation sequencing technologies and bioinformatics have permitted the exploration and identification of various non-coding regions of the genome other than protein coding genes. These genomic regions produce various types of non-coding RNAs and regulate myriads of biological functions at epigenetic, transcriptional and translational levels. Recently, long non-coding RNAs (lncRNAs) which act as molecular switch have been identified to be pivotal molecules in forest trees. This review focuses on progress made in regulatory mechanisms in various developmental phases like wood formation, adventitious rooting and flowering and stress responses. It was predicted that complex regulatory interactions among lncRNA, miRNA and gene exist. LncRNAs can function as a sponge for miRNAs, reducing the suppressive effect of miRNAs on target mRNAs and perhaps adding a new layer of regulatory interactions among non-coding RNA classes in trees. Furthermore, network analysis revealed the interactions of lncRNA and genes during the expression of several important genes. The insights generated about lncRNAs in forest trees would enable improvement of economically important traits including the devastating abiotic and biotic stresses. In addition, solid understanding on the wide range of regulatory functions of lncRNAs on traits influencing biomass productivity and adaptation would aid the applications of biotechnology in genetic improvement of forest trees.

Pursuit of precision medicine: Systems biology approaches in Alzheimer's disease mouse models

Alzheimer's disease (AD) is a complex disease that is mediated by numerous factors and manifests in various forms. A systems biology approach to studying AD involves analyses of various body systems, biological scales, environmental elements, and clinical outcomes to understand the genotype to phenotype relationship that potentially drives AD development. Currently, there are many research investigations probing how modifiable and nonmodifiable factors impact AD symptom presentation. This review specifically focuses on how imaging modalities can be integrated into systems biology approaches using model mouse populations to link brain level functional and structural changes to disease onset and progression. Combining imaging and omics data promotes the classification of AD into subtypes and paves the way for precision medicine solutions to prevent and treat AD.