We used Illumina Human HT-12 v4 arrays to compare RNA expression of middle temporal gyrus (MTG; BA21) in Alzheimer’s disease (AD = 97) and non-demented controls (ND = 98). A total of 938 transcripts were highly differentially expressed (adj p < 0

The clinical diagnosis of neurodegenerative diseases is notoriously inaccurate and current methods are often expensive, time-consuming, or invasive. Simple inexpensive and noninvasive methods of diagnosis could provide valuable support for clinicians when combined with cognitive assessment scores. Biological processes leading to neuropathology progress silently for years and are reflected in both the central nervous system and vascular peripheral system. A blood-based screen to distinguish and classify neurodegenerative diseases is especially interesting having low cost, minimal invasiveness, and accessibility to almost any world clinic. In this study, we set out to discover a small set of blood transcripts that can be used to distinguish healthy individuals from those with Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, amyotrophic lateral sclerosis, Friedreich’s ataxia, or frontotemporal dementia. Using existing public datasets, we developed a machine learning algorithm for application on transcripts present in blood and discovered small sets of transcripts that distinguish a number of neurodegenerative diseases with high sensitivity and specificity. We validated the usefulness of blood RNA transcriptomics for the classification of neurodegenerative diseases. Information about features selected for the classification can direct the development of possible treatment strategies.

Alzheimer’s disease is a neurodegenerative disorder clinically defined by gradual cognitive impairment and alteration in executive function. We conducted an epigenome-wide association study (EWAS) of a clinically and neuropathologically characterized cohort of 296 brains, including Alzheimer’s disease (AD) and non-demented controls (ND), exploring the relationship with the RNA expression from matched donors. We detected 5246 CpGs and 832 regions differentially methylated, finding overlap with previous EWAS but also new associations. CpGs previously identified in ANK1, MYOC, and RHBDF2 were differentially methylated, and one of our top hits (GPR56) was not previously detected. ANK1 was differentially methylated at the region level, along with APOE and RHBDF2. Only a small number of genes showed a correlation between DNA methylation and RNA expression statistically significant. Multiblock partial least-squares discriminant analysis showed several CpG sites and RNAs discriminating AD and ND (AUC = 0.908) and strongly correlated with each other. Furthermore, the CpG site cg25038311 was negatively correlated with the expression of 22 genes. Finally, with the functional epigenetic module analysis, we identified a protein–protein network characterized by inverse RNA/DNA methylation correlation and enriched for “Regulation of insulin-like growth factor transport”, with IGF1 as the hub gene. Our results confirm and extend the previous EWAS, providing new information about a brain region not previously explored in AD DNA methylation studies. The relationship between DNA methylation and gene expression is not significant for most of the genes in our sample, consistently with the complexities in the gene expression regulation. Graphical Abstract

The ability to perform highly sensitive and multiplexed in-situ protein analysis is crucial to advance our understanding of normal physiology and disease pathogenesis. To achieve this goal, we here develop an approach using cleavable biotin-conjugated antibodies and cleavable fluorescent streptavidin (CFS). In this approach, protein targets are first recognized by the cleavable biotin-labeled antibodies. Subsequently, CFS is applied to stain the protein targets. Though layer-by-layer signal amplification using cleavable biotin-conjugated orthogonal antibodies and CSF, the protein detection sensitivity can be enhanced at least 10-fold, compared with the current in-situ proteomics methods. After imaging, the fluorophore and the biotin unbound to streptavidin are removed by chemical cleavage. The leftover streptavidin is blocked by biotin. Upon reiterative analysis cycles, a large number of different proteins with a wide range of expression levels can be profiled in individual cells at the optical resolution. Applying this approach, we have demonstrated that multiple proteins are unambiguously detected in the same set of cells, regardless of the protein analysis order. We have also shown that this method can be successfully applied to quantify proteins in formalin-fixed paraffin-embedded (FFPE) tissues.