Identification of Unstable Network Modules Reveals Disease Modules Associated with the Progression of Alzheimer’s Disease

<div><p>Alzheimer’s disease (AD), the most common cause of dementia, is associated with aging, and it leads to neuron death. Deposits of amyloid β and aberrantly phosphorylated tau protein are known as pathological hallmarks of AD, but the underlying mechanisms have not yet been revealed. A high-throughput gene expression analysis previously showed that differentially expressed genes accompanying the progression of AD were more down-regulated than up-regulated in the later stages of AD. This suggested that the molecular networks and their constituent modules collapsed along with AD progression. In this study, by using gene expression profiles and protein interaction networks (PINs), we identified the PINs expressed in three brain regions: the entorhinal cortex (EC), hippocampus (HIP) and superior frontal gyrus (SFG). Dividing the expressed PINs into modules, we examined the stability of the modules with AD progression and with normal aging. We found that in the AD modules, the constituent proteins, interactions and cellular functions were not maintained between consecutive stages through all brain regions. Interestingly, the modules were collapsed with AD progression, specifically in the EC region. By identifying the modules that were affected by AD pathology, we found the transcriptional regulation-associated modules that interact with the proteasome-associated module via UCHL5 hub protein, which is a deubiquitinating enzyme. Considering PINs as a system made of network modules, we found that the modules relevant to the transcriptional regulation are disrupted in the EC region, which affects the ubiquitin-proteasome system.</p> </div

The process used to generate the module lineages.

<p>(A) Calculation of the interactions (C_L) of all possible module pairs in two consecutive stages. (B) Of the module pairs exhibiting the highest <i>C</i>_<i>L</i>, if <i>C</i>_<i>L</i> and <i>C</i>_<i>GO</i> exceeded 0.5, the modules were considered “inherited.” (C) If the modules were inherited from the earliest age group or AD progression stage (60–69 y/o or Braak stage I) to the latest age group or AD progression stage (90–99 y/o or Braak stage IV in the EC region or Braak stage VI in the HIP and the SFG regions), we called these modules “inherited-module lineages,” and called the other modules “disrupted inherited-module lineages.” Each node indicates distinct modules. Thick links are the module pairs exhibiting the highest CL. Arrows represent inherited relationships.</p

Flowchart for the identification of expressed protein interaction networks (PINs) and the detection of module.

<p>Expressed proteins were extracted from gene expression profiles based on our criteria: detection call is “present” and the average expression value is more than 200. Merging the list of expressed proteins and protein-protein interaction data, we obtained interactions whose constituent proteins were expressed at the same time as expressed protein interactions, and we constructed expressed PINs. We then detected modules from expressed PINs by using the Infomap algorithm. These processes were also performed in the other brain regions.</p

A scheme of appearing and disappearing interactions.

<p>An appearing interaction was defined as an expressed protein interaction that was not expressed at an early age or stage of AD progression but was expressed in later stages and age groups. A disappearing interaction was defined as an expressed protein interaction that was expressed at an early age or AD progression stage but was not expressed in later stages or age groups. Each interaction has three patterns indicated in a scheme.</p

Schematic illustration of AD-disrupted modules.

<p>AD-disrupted modules were classified as the early-disrupted type or the late-disrupted type. Red nodes: modules in normal aging. Blue nodes: modules in AD. Black lines: inherited relationships in normal aging. Red lines: correspondences between the module in each age group in normal aging and the module in the corresponding Braak stage in AD.</p

Ratios of appearing and disappearing interactions.

<p>Red plots indicate the ratios of appearing protein interactions, and blue plots indicate disappearing protein interactions. The boxplots indicate the ratios of appearing and disappearing protein interactions from 1,000 corresponding randomized networks in each brain region in normal aging and AD. Values below the boxplots show the Z-scores between the ratio and the ratios of 1,000 randomized networks. The ratio of the number of disappearing interactions in the AD entorhinal cortex (EC) region showed no significant difference from those of the 1,000 randomized networks (Z-score = −0.671).</p

Auto-correlations of proteins, interactions, and functions for inherited modules.

<p>Probability density distributions of the (A) auto-correlation of proteins, (B) interactions, and (C) cellular functions of a consecutive module pair. Orange curves indicate normal aging and green curves indicate AD. P-values were calculated from the Wilcoxon test. Auto-correlations in AD were significantly lower than those in normal aging through all brain regions.</p

Additional file 2: Table S1. of Serum microRNA miR-501-3p as a potential biomarker related to the progression of Alzheimer’s disease

Top 20 deregulated serum miRNAs that were identified by NGS in the ROW discovery set after adjusting for age, sex, APOE genotype, and hemolysis ratio. Table S2. Significantly deregulated miRNAs that were identified by NGS in the temporal cortex of the ROW discovery set. Table S3. Significantly deregulated miRNAs that were identified by NGS in the temporal cortex of the ROW discovery set after adjusting for age, sex, APOE genotype, and RIN. Table S4. Significantly differentially expressed genes that were identified by NGS in hsa-miR-501-3p overexpression in cultured cells. Table S5. Gene Ontology enrichment analysis on the significantly downregulated genes in hsa-miR-501-3p overexpression in cultured cells. Table S6. Gene Ontology enrichment analysis on the significantly upregulated genes in hsa-miR-501-3p overexpression in cultured cells. (XLS 172 kb

Additional file 1: Figure S1. of Serum microRNA miR-501-3p as a potential biomarker related to the progression of Alzheimer’s disease

This study’s definitions of patients with Alzheimer’s disease (AD) and controls on the basis of Braak staging in the ROW discovery set. (PDF 186 kb

Additional file 4 of Amygdala granular fuzzy astrocytes are independently associated with both LATE neuropathologic change and argyrophilic grains: a study of Japanese series with a low to moderate Braak stage

Additional file 4: Fig. S2. TDP-43 pathology, granular fuzzy astrocytes (GFAs), argyrophilic grains, hippocampal sclerosis, and tissue degeneration in the amygdala in representative cases. A–F Pathological findings in a case with Braak NFT stage II, Thal phase 0, amygdala GFA stage 2, Saito AG stage III, and LATE-NC stage 2. A, B Phosphorylated TDP-43 accumulation in the amygdala A and dentate gyrus in the hippocampus B. pS409/410 immunohistochemistry. Scale bar: 25 μm. C A GFA in the amygdala. AT8 immunohistochemistry. Scale bar: 25 μm. D AGs in the amygdala. Gallyas method. Scale bar: 25 μm. E Hippocampal sclerosis. Hematoxylin-eosin stain. Scale bar: 100 μm. F Severe loss of neurons with gliosis in the amygdala. Hematoxylin-eosin stain. Scale bar: 25 μm. G–L Pathological findings in a case with Braak stage II, Thal phase 0, amygdala GFA stage 4, Saito AG stage III, and LATE-NC stage 0. G This case lacked phosphorylated TDP-43-positive lesion in any region. The amygdala. pS409/410 immunohistochemistry. Scale bar: 25 μm. H, I GFAs in the amygdala. AT8 immunohistochemistry. Scale bar: 25 μm. J AGs in the amygdala. Gallyas method. Scale bar: 25 μm. K Neither loss of pyramidal neurons nor gliosis is noted in the hippocampal CA1. Hematoxylin-eosin stain. Scale bar: 100 μm. L Severe neuronal loss with gliosis in the amygdala. Hematoxylin-eosin stain. Scale bar: 25 μm