Abstract
Despite huge investments and major efforts to develop remedies for Alzheimer’s disease (AD) in the past decades, AD remains incurable. While evidence for molecular and phenotypic variability in AD have been accumulating, AD research still heavily relies on the search for AD-specific genetic/protein biomarkers that are expected to exhibit repetitive patterns throughout all patients. Thus, the classification of AD patients to different categories is expected to set the basis for the development of therapies that will be beneficial for subpopulations of patients. Here we explore the molecular heterogeneity among a large cohort of AD and non-demented brain samples, aiming to address the question whether AD-specific molecular biomarkers can progress our understanding of the disease and advance the development of anti-AD therapeutics. We studied 951 brain samples, obtained from up to 17 brain regions of 85 AD patients and 22 non-demented subjects. Utilizing an information-theoretic approach, we deciphered the brain sample-specific structures of altered transcriptional networks. Our in-depth analysis revealed that 7 subnetworks were repetitive in the 737 diseased and 214 non-demented brain samples. Each sample was characterized by a subset consisting of ~1–3 subnetworks out of 7, generating 52 distinct altered transcriptional signatures that characterized the 951 samples. We show that 30 different altered transcriptional signatures characterized solely AD samples and were not found in any of the non-demented samples. In contrast, the rest of the signatures characterized different subsets of sample types, demonstrating the high molecular variability and complexity of gene expression in AD. Importantly, different AD patients exhibiting similar expression levels of AD biomarkers harbored distinct altered transcriptional networks. Our results emphasize the need to expand the biomarker-based stratification to patient-specific transcriptional signature identification for improved AD diagnosis and for the development of subclass-specific future treatment.
Highlights
Alzheimer’s disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline and neurodegeneration
Up to 17 different brain regions were sampled in each patient: frontal pole (FP), occipital visual cortex (OVC), inferior temporal gyrus (ITG), middle temporal gyrus (MTG), superior temporal gyrus (STG), posterior cingulate cortex (PCC), anterior cingulate (AC), parahippocampal gyrus (PG), temporal pole (TP), precentral gyrus (PrG), inferior frontal gyrus (IFG), dorsolateral prefrontal cortex (DPC), superior parietal lobule (SPL), prefrontal cortex (PC), caudate nucleus (CN), hippocampus (Hi) and putamen (Pu)
We found that the brain of each AD patient can harbor several barcodes, each representing a different region in the brain, unraveling an additional layer of complexity existing in AD disease (Figure 6A, an example for subject 111 is shown; the complete information for all subjects in the dataset is presented in Table S4, tab “Sample-specific barcodes”, summarizing the barcodes’ appearances in each brain region and pathological condition)
Summary
Alzheimer’s disease (AD) is the most common cause of dementia, characterized by progressive cognitive decline and neurodegeneration. AD is defined pathologically by the presence of senile plaques and neurofibrillary tangles (NFTs), in the hippocampus and neocortex [1]. According to the amyloid hypothesis [3], AD develops as a result of the hyper activation of two proteolytic entities, the β and γ secretases, which both digest the amyloid precursor protein (APP). This dual digestion results in increased production of the family of aggregative amyloid β (Aβ) peptides, which in turn cause neuronal death and underlie the development of AD. A careful analysis of familial AD (fAD)-causing mutations in the sequence of presenilin 1 (PS1), an aspartic protease which possesses the activity of the γ secretase complex, unveils that many fAD-causing mutations lead to loss of PS1 function [4,5], thereby contradicting the amyloid hypothesis
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