Effects of DISC1 on Alzheimer's disease cell models assessed by iTRAQ proteomics analysis

Subcellular proteomics insights into Alzheimer's disease development

Alzheimer's disease (AD), one of the most common dementias, is a neurodegenerative disease characterized by cognitive impairment and decreased judgment function. The expected number of AD patient is increasing in the context of the world's advancing medical care and increasing human life expectancy. Since current molecular mechanism studies on AD pathogenesis are incomplete, there is no specific and effective therapeutic agent. Mass spectrometry (MS)-based unbiased proteomics studies provide an effective and comprehensive approach. Many advances have been made in the study of the mechanism, diagnostic markers, and drug targets of AD using proteomics. This paper focus on subcellular level studies, reviews studies using proteomics to study AD-associated mitochondrial dysfunction, synaptic, and myelin damage, the protein composition of amyloid plaques (APs) and neurofibrillary tangles (NFTs), changes in tissue extracellular vehicles (EVs) and exosome proteome, and the protein changes in ribosomes and lysosomes. The methods of sample separation and preparation and proteomic analysis as well as the main findings of these studies are involved. The results of these proteomics studies provide insights into the pathogenesis of AD and provide theoretical resource and direction for future research in AD, helping to identify new biomarkers and drugs targets for AD.

Unified epigenomic, transcriptomic, proteomic, and metabolomic taxonomy of Alzheimer's disease progression and heterogeneity

Alzheimer's disease (AD) is a heterogeneous disorder with abnormalities in multiple biological domains. In an advanced machine learning analysis of postmortem brain and in vivo blood multi-omics molecular data (N = 1863), we integrated epigenomic, transcriptomic, proteomic, and metabolomic profiles into a multilevel biological AD taxonomy. We obtained a personalized multilevel molecular index of AD dementia progression that predicts severity of neuropathologies, and identified three robust molecular-based subtypes that explain much of the pathologic and clinical heterogeneity of AD. These subtypes present distinct patterns of alteration in DNA methylation, RNA, proteins, and metabolites, identifiable in the brain and subsequently in blood. In addition, the genetic variations that predispose to the various AD subtypes in brain predict distinct spatial patterns of alteration in cell types, suggesting a unique influence of each putative AD variant on neuropathological mechanisms. These observations support that an individually tailored multi-omics molecular taxonomy of AD may represent distinct targets for preventive or treatment interventions.

Transcriptional profiles in olfactory pathway-associated brain regions of African green monkeys: Associations with age and Alzheimer's disease neuropathology

Introduction

Olfactory impairment in older individuals is associated with an increased risk of Alzheimer's disease (AD). Characterization of age versus neuropathology-associated changes in the brain olfactory pathway may elucidate processes underlying early AD pathogenesis. Here, we report age versus AD neuropathology-associated differential transcription in four brain regions in the olfactory pathway of 10 female African green monkeys (vervet, Chlorocebus aethiops sabaeus), a well-described model of early AD-like neuropathology.

Methods

Transcriptional profiles were determined by microarray in the olfactory bulb (OB), piriform cortex (PC), temporal lobe white matter (WM), and inferior temporal cortex (ITC). Amyloid beta (Aβ) plaque load in parietal and temporal cortex was determined by immunohistochemistry, and concentrations of Aβ42, Aβ40, and norepinephrine in ITC were determined by enzyme-linked immuosorbent assay (ELISA). Transcriptional profiles were compared between middle-aged and old animals, and associations with AD-relevant neuropathological measures were determined.

Results

Transcriptional profiles varied by brain region and age group. Expression levels of TRO and RNU4-1 were significantly lower in all four regions in the older group. An additional 29 genes were differentially expressed by age in three of four regions. Analyses of a combined expression data set of all four regions identified 77 differentially expressed genes (DEGs) by age group. Among these DEGs, older subjects had elevated levels of CTSB , EBAG9, LAMTOR3, and MRPL17, and lower levels of COMMD10 and TYW1B. A subset of these DEGs was associated with neuropathology biomarkers. Notably, CTSB was positively correlated with Aβ plaque counts, Aβ42:Aβ40 ratios, and norepinephrine levels in all brain regions.

Discussion

These data demonstrate age differences in gene expression in olfaction-associated brain regions. Biological processes exhibiting age-related enrichment included the regulation of cell death, vascular function, mitochondrial function, and proteostasis. A subset of DEGs was specifically associated with AD phenotypes. These may represent promising targets for future mechanistic investigations and perhaps therapeutic intervention.