A Big Data Look at Alzheimer's Disease, Part I

 

Here, we’ll take on Alzheimer’s disease. The subject is huge, of course, so we’ll devote future posts to Alzheimer’s as well. For the near term, we’d like to make the following points:

1. Mouse Alzheimer’s models and EAE (neuroinflammation) models overlap quite significantly, at least when examining upregulated (vs. downregulated) transcripts.
2. Hooray for mouse models, right? Actually, maybe not. That’s because the mouse Alzheimer’s and EAE models fail to intersect with transcripts altered in actual human Alzheimer’s brain tissues.
3. Somatostatin stands out in our analysis as the most consistently altered transcript in the human Alzheimer’s brain.
4. Hoxa5 may be relevant to Alzheimer’s.
5. A study with antiretrovirals may hint at a treatment option.

To tackle the topic, we constructed a number of “canonical” regulation lists. First, there are lists of transcripts that are up/down-regulated in real human Alzheimer’s cases, when compared to healthy control brains. We used a total of 35 different transcriptomic studies to construct the upregulation and downregulation lists. The database IDs for these lists are 123049121 and 123050121. Similarly, we constructed canonical lists for transcripts altered in mouse Alzheimer’s model brains (12 studies: 123633121 and 123634121) and in mouse EAE model brains (8 studies: 123635121 and 123636121). We also built up/down-regulation lists for transcripts altered in the blood of Alzheimer’s patients (123069121 and 123070121); these blood-focused lists are not particularly relevant to this post, but you may wish to tinker with them anyway using the apps at WhatIsMyGene.

Let’s look at upregulation in the three relevant canonical lists:

Had this post been an academic paper, that Venn (via interactivenn.net) would have consumed half a day. Instead; about 3 minutes. It’s easy to see that, from the big-data transcriptomic point of view, the mouse Alzheimer’s models, most (but not all) of which utilize overexpression of amyloid beta precursor, have no relevance to human Alzheimer’s. The same goes for the EAE (experimental autoimmune encephalitis) mouse studies. Of note, the single transcript found at the intersection of human Alzheimer’s and the EAE studies is SERPINA3. The P-value for the mouse Alzheimer’s model/EAE model intersection works out to about 10^-20.

For the sake of argument, let’s pretentiously assume that our own big-data approach invalidates the notion that mouse AD models and EAE studies have anything to do with Alzheimer’s in humans. Why, then, has so much been invested in the mouse studies? Without immersing myself in the literature, I’d offer up several points:

•     Amyloid plaque is the most obvious hallmark of Alzheimer’s. It makes sense to induce these plaques in mice (via knock-ins). These plaques, in turn, induce hallmarks of EAE.
•     Some evidence suggests that neuroinflammation may positively correlate with Alzheimer’s in humans. For example, numerous studies show an inverse correlation between rheumatoid arthritis and Alzheimer’s, with researchers speculating that the use of various anti-inflammatories may provide the crucial link.
•     Some human neurological diseases indeed overlap with both Alzheimer’s and the mouse models and EAE studies. For example, multiple sclerosis offers parallels with both human Alzheimer’s and EAE, and Creutzfeldt-Jakob brains offer parallels with both human Alzheimer’s and the mouse Alzheimer’s models.

Thus, it’s easy to assume that the mouse experiments are moving the field in the correct direction. However, to refute the above points:

•     It’s apparent that the plaques cause neuroinflammation, not the inverse (i.e. knock in APP and generate a mouse with neuroinflammation).
•     Unfortunately, recent studies have blurred the correlations between arthritis, anti-inflammatories, and Alzheimer’s. Even assuming that the negative correlation between RA and Alzheimer’s holds, some have questioned whether anti-inflammatories are the molecules that counter neuro-degeneration.
•     Connecting Alzheimer’s with EAE, using multiple sclerosis or Creutzfeldt-Jakob studies as an “intermediary”, is like children playing the game of “telephone.” A lot can get lost in translation. As an example, look below. Transcripts upregulated in Creutzfeldt-Jakob brains (PMID 30446946) overlap strongly with those upregulated in Alzheimer’s, and the Creutzfeldt-Jakob data overlaps nicely with mouse Alzheimer models (-log(P) of approximately 20 and 12, respectively). This doesn’t alter the nonexistent connection between mouse models and human Alzheimer’s, however.

On the positive side, it’s possible that therapies that remediate plaques in mice might be beneficial for Creutzfeldt-Jakob patients. The mouse Alzheimer’s models are relevant to human disease, but perhaps not human Alzheimer’s.

One simple point: Note that we do find human/mouse overlap between two neurodegenerative conditions. One needn't wonder if somehow our algorithms are failing to convert mouse identifiers to their orthologous human counterparts. 

Below is a Venn diagram examining downregulated transcripts in the three “canonical” lists:

Here, the three sets show even less relevance to each other. If you’re interested, the three transcripts found in the human Alzheimer/mouse model intersection are NPTX2, DUSP6, and PCSK1.

Note Jan 2021: How did I miss this?...Mouse models rarely mimic the transcriptome of human neurodegenerative diseases: A systematic bioinformatics-based critique of preclinical models. A 2015 paper that has apparently been ignored for the most part.

Looking at the subject from a purely transcriptomic/big-data view, it would seem that amyloid plaques are a by-product of Alzheimer’s pathology.

We’ve covered our initial points 1) and 2). We’ll address the next three points, and more, in upcoming posts.

whatismygene.com 

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