Your Christmas Gift: Neural Disorders

 

Tinkering with Alzheimer’s data, I noticed that Somatostatin, the most commonly downregulated protein in Alzheimer’s studies, was also downregulated in the brains of alcoholics and bipolar disorder patients. This was somewhat bothersome; could many or most of the genes I had identified as Alzheimer’s markers simply be broad markers for neural conditions in general? I thus constructed new “canonical” lists for brain conditions with at least a handful of post-mortem studies, and compared these to the canonical Alzheimer’s list. Specifically, we have up/downregulation lists for Parkinson’s (database IDs 124415121 and 124416121), alcoholism (124416121 and 124416122), schizophrenia (124417121 and 124418121), depression/bipolar disorder (124419121 and 124419122), and autism (124420121 and 124421121).

Intersecting studies with studies, one gets P-values via Fisher’s exact test. Below, red signifies strong intersections (beginning at –log(P)>4 and as high as 91), white gives intersections with weak statistical significance, and blue signifies weak anti-correlation (in no cases was anti-correlation particularly significant*). To answer the initial question: no, most genes in our canonical lists are found in only one list; there’s no single set of genes that typifies neural disorders.

 

A	upregulated in frontal cortex of Creutzfeldt-Jakob patients (GSE124571)
B	downregulated in frontal cortex of Creutzfeldt-Jakob patients (GSE124571)
C	upregulated in midbrain of cocaine-addicted subjects (GSE54839)
D	downregulated in midbrain of cocaine-addicted subjects (GSE54839)
E	upregulated in postmortem brains of hiv patients w/neurocognitive disorders who took ARVs (GSE28160)
F	downregulated in postmortem brains of hiv patients w/neurocognitive disorders who took ARVs (GSE28160)
G	canonically upregulated in blood of alzheimer's patients (n=2)
H	canonically downregulated in blood of alzheimer's patients (n=2)
I	canonical up in mouse brain alzheimer's model (12 studies; n>=3)
J	canonical down in mouse brain alzheimer's model (12 studies; n>=2)
K	canonical up in mouse eae brain (8 studies; n>=4)
L	canonical down in mouse eae brain (8 studies; n>=2)
M	canonical up in Parkinson's brain (5 studies; n=2)
N	canonical down in Parkinson's brain (5 studies; n>=2)
O	canonical up in alcoholic brain (4 studies; n>=3)
P	canonical down in alcoholic brain (4 studies; n>=2)
Q	canonical up in schizophrenia brain (17 studies; n>=3)
R	canonical down in schizophrenia brain (17 studies; n>=3)
S	canonical up in depression/bipolar brain (8 studies; n>=2)
T	canonical down in depression/bipolar brain (8 studies; n>=2)
U	canonical up in human Alzheimer's brain (found in at least 5 of 35 studies)
V	canonical down in human Alzheimer's brain (found in at least 5 of 35 studies)
W	canonical up in autism brain (5 studies; n=2)
X	canonical down in autism brain (5 studies; n=2)

What are the genes that are found in two or more of the “canonical” lists?

down Alcoholism/Alzheimer's/Autism/Bipolar/Parkinsons PCSK1 up Alcoholism up Autism up Schizophrenia up bipolar SLC14A1 down Alcoholism down Alzheimer's up Parkinsons GAD2 up Alcoholism up Schizophrenia up bipolar S100A8 SDC4 up Alcoholism up Alzheimer's up Schizophrenia SERPINA3 down Parkinsons up Autism up Schizophrenia FGF13 down Alcoholism down Alzheimer's down Parkinsons DCLK1 down Alcoholism down Alzheimer's down Bipolar SST NEUROD6 CRH GAD1 TAC1 RGS4 down Alcoholism down Alzheimer's down Autism GABRG2 up Alcoholism up Schizophrenia MT2A FAM107A up Alcoholism up bipolar MT1X up Alcoholism up Alzheimer's ITPKB DTNA MT1M up Alcoholism up Autism IFITM2 up Schizophrenia up bipolar ETNPPL GJA1 CHI3L1 PPAP2B AQP4 NFKBIB up Alzheimer's up Schizophrenia FKBP5 CALD1 up Autism up Schizophrenia SLC1A3 down Alcoholism up Schizophrenia GLS2 down Alzheimer's up Schizophrenia TUBB2B up Alzheimer's up bipolar AQP1 MT1H up Autism up bipolar PDGFRA down Parkinsons up bipolar PCDH8 down Alzheimer's up bipolar WIF1 CALB1 up Alzheimer's up Autism VCAN down Alcoholism up Alzheimer's ANLN down Bipolar up Alzheimer's DUSP1 down Schizophrenia up Autism SOCS3 down Alzheimer's down Parkinsons CIRBP down Alcoholism down Schizophrenia MOG down Alcoholism down Bipolar FOS SSX2IP GPR37 down Alcoholism down Alzheimer's NELL1 CAP2 STMN2 B4GALT6 GABRA1 CRYM NCALD RAB3B CHGB GLRB NEFL INA down Alcoholism down Autism MB down Bipolar down Schizophrenia TNFSF10 DNAJB5 down Alzheimer's down Schizophrenia CBLN4 down Alzheimer's down Bipolar DUSP6 ATP6AP2 NPTX2 EGR1 RPH3A down Alzheimer's down Autism STAT4

The heatmap and the list of intersecting genes** offer a lot of food for thought. Some of the most obvious observations have been made in previous posts. For example, mouse Alzheimer’s models do a lousy job of paralleling human Alzheimer’s, though they may be relevant to other disorders (e.g. bipolar disorder and Creutzfeldt-Jakob disease). The antiretroviral results remain the most eye popping of all; no amount of Bonferroni correction can hide those P-values. It’s interesting to note that PCSK1 is downregulated in 5 of the 7 human brain-centered lists. SLC14A1 is seen in 4 lists. No others are seen more than 3 times.

We’ve highlighted genes that are upregulated in one list, but downregulated in others. Of 70 genes found in canonical list intersections, 10 fall into this category. One might give special importance to these genes, speculating that various disorders “hinge” on their expression. At the same time, folks who are interested in defining the causes of particular neural maladies may wish to de-emphasize the remaining 60 genes on the assumption that they are “responders” to messed-up chemistry, not causative. One relevant caveat would be the fact that our canonical lists are created by combining studies that probed a number of brain regions. Thus we treat the brain as a single entity, not an organ with a myriad of distinct cell types, and it’s still possible, for example, that ITPKB would be a very specific marker for Alzheimer’s if you focused exclusively on the hippocampus. 

We’ll dish out a few more posts on the subject of Alzheimer’s, and then move on to new subjects (the effects of prolonged vibration of mice? The blood transcriptome of meditating monks? Or just jump into another heavy topic, like cancer or cytokine storms?)

*We should point out that it's difficult to identify strong anti-correlation. If you have 20,000 genes, and two randomly-derived subsets of 100 genes, it's not at all interesting if there's no intersection between the two subsets. If you want to see anti-correlation, you need long lists. Our canonical lists are quite short. Thus, strong anti-correlations may exist, with the blue color hinting at them.

**You can't make a single Venn diagram with 14 lists, but there is a nice Venn-diagram tool that will nevertheless detail all of the different intersecting groups.

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Alzheimer's Part III: Antiretrovirals

Previously, we mentioned the relevance of antiviral therapy to Alzheimer’s disease. Specifically, we’re looking at a 2011 study, Significant Effects of Antiretroviral Therapy on Global Gene Expression in Brain Tissues of Patients with HIV-1-Associated Neurocognitive Disorders, in which post-mortem brains of HIV patients were compared according to several parameters, one of them being the usage of antiretrovirals. Utilizing our lists of transcripts that are canonically up/down-regulated in Alzheimer’s, one sees an impressive alteration of these transcripts on antiretroviral therapy:

The P-values work out to about 10^-4 and 10^-43. You can go through the exercise yourself: just choose the “Match Studies” tool, input the IDs for the two “canonical” Alzheimer’s lists (123049121 and 123050121), choose “drug” under “Experiment Type”, and choose “Inverse Correlations” (that way, you’ll be looking for datasets that counter Alzheimer’s). The ensuing “p_multiple” is simply the result of multiplying -4 * -43.

Here are transcripts at the intersections:

up-Alz/down antiretrovirals		down-Alz/up antiretrovirals
APLNR		ARPP21	ELAVL4	NEFL	SNAP25
CD163		B4GALT6	GABRA1	NEFM	SST
CD44		BEX5	GABRG2	NELL2	STMN2
CXCR4		CADPS	GAD1	NRN1	SV2B
NUPR1		CALB1	GLRB	NRXN1	TSPAN7
SERPINA3		CAP2	GNG3	NSG2	VSNL1
		COPG2IT1	HCN1	OLFM3
		CPNE4	HOPX	RGS4
		DCLK1	INA	RPH3A
		DIRAS2	KCNIP4	SCN3B

If you use our tool as above, you’ll note that there really are no other treatments with this profound effect. Next in line, somewhat surprisingly, would be a study in which neuroinflammation was induced in mice retinas!

Now, we cannot simply conclude that antiretrovirals would be effective against Alzheimer’s. We note that the single best drug that mimics the transcriptomic effects of Alzheimer’s is cocaine. A Google Scholar search, however, reveals no connections between cocaine use and Alzheimer’s. Drugs that cause Alzheimer’s –like transcriptomic effects don’t necessarily cause Alzheimer’s; drugs that reverse Alzheimer’s transcriptomic effects cannot be assumed to work as treatments.

Are there other studies in our database in which brain tissue was examined following the use of antiretrovirals? There’s one, an apparently unpublished rhesus study with GEO accession GSE117336. In this case, there aren’t any interesting correlations with our Alzheimer’s lists.

However, let’s take the human results at face value for the moment. The simplest conclusion would be that Alzheimer’s is caused by a viral infection. Such a view cannot be considered “fringe”, but neither is it a leading hypothesis. Naturally, there are results both supporting and disputing the Alzheimer’s/virus link. Most of the studies supporting the link refer to herpes virus, which is not a retrovirus and does not seem to be strongly inhibited by antiretrovirals. Alternatively, the antiretrovirals may be acting upon a host-intrinsic process. Retrotransposition? Here, one paper may be particularly relevant: Somatic APP gene recombination in Alzheimer’s disease and normal neurons. In addition to suggesting mechanisms by which retrotransposition may relate to Alzheimer’s, the paper also points out a low incidence of Alzheimer’s in HIV patients on antiretrovirals!

One should bear in mind that there are, in a sense, two variables being tweaked in the antiretroviral study; the application of a drug, and the load of a virus. Thus it is possible that the untreated patients are progressing to an Alzheimer's like-state with great rapidity, and the antiretroviral drugs are not actually "reversing" any neuropathology. In this case, the question is not "how are the antiretrovirals working?", but "how does HIV cause Alzheimer's-like transcriptomics?"

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Alzheimer’s Part II: Somatostatin and More

Previously, we briefly described the construction of our “canonical” lists of up/down-regulated transcripts in the human Alzheimer’s brain. We also mentioned somatostatin (SST) as a gene that stood out. That’s because in 35 studies examining the Alzheimer’s brain, SST was downregulated 13 times. No other transcript was up- or down-regulated that many times. Below is a look at the most altered transcripts in the two lists: 

upregulated in canonical Alzheimer's	count		downregulated in canonical Alzheimer's	count
ITPKB	12		SST	13
GFAP	11		RGS4	12
AEBP1	10		SVOP	11
APLNR	10		PCSK1	11
CD44	8		RPH3A	10
NUPR1	8		CARTPT	10
p8	8		CRYM	9
CHST6	8		STMN2	9
AQP1	7		GABRG2	9
SLC7A2	7		NRN1	9
AHNAK	7		GAD1	9
SERPINA3	7		INA	9
			VSNL1	9
			BEX5	9

If we adjust gene counts for the frequency with which they appear in brain-related studies in our database, the basic picture above does not change radically. SST falls, however, to 3^rd in importance and SVOP rises to #1. In terms of upregulated genes, ITPKB retains its position, but GFAP falls to #6.

Though our "canonical" lists are purely transcriptomic, our database does contain a few proteomic studies relating to Alzheimer's. In one recent study, Quantitative Proteomic Analysis of the Frontal Cortex in Alzheimer's Disease, somatostatin was the single most strongly downregulated protein. What's more, which of the lists within our database best intersected downregulated proteins in this study? Our "canonically downregulated in Alzheimer's list", with a -log(P) of 4! So much for the dogma that transcriptomic and proteomic results show little or no correlation.

In general, significantly downregulated transcripts outnumber significantly upregulated transcripts in the two canonical lists. 28 transcripts appear at least 8 times in the downregulation list, while only 8 transcripts appear 8 or more times in the upregulation list. This is the opposite of the case in mouse Alzheimer and EAE models, where upregulation dominates. 

Somatostatin certainly has been mentioned in the context of Alzheimer’s. In one MS study, the short (14 aa) form of SST was found to bind oligomeric amyloid plaques (Somatostatin binds to the human amyloid beta peptide and favors the formation of distinct oligomers). The authors of this paper followed up with a review summarizing the somatostatin/Alzheimer’s link (Somatostatin in Alzheimer's disease: A new Role for an Old Player). Other reviews and research papers on the subject can be found.

Given the presence of “Somatostatinopathies”, there are indeed drugs designed to compensate for low somatostatin levels in various tissues. Here’s a recent example of an SST analog altering plaque pathology in mice: Enhanced neprilysin-mediated degradation of hippocampal Aβ42 with a somatostatin peptide that enters the brain.

We mentioned the possible relevance of antiretroviral therapy to Alzheimer’s disease in our previous post. We’ll delve deeper into the topic later, but for now, we note that antiretrovirals (see PMID 21909266) are the only drugs in our database that specifically upregulate SST in the brain (to see for yourself, select the WhatIsMyGene “relevant studies” app, enter “sst”, choose “upregulation” under “Regulation”, and “Drug” under “Study Type”). Ignoring brain-specific studies, one can find a number of compounds that seem to upregulate SST (Vitamin D is one, at least in the colon).

Note 12/16/2020: We've stumbled across a few more drugs that may increase SST levels in the brain: propanolol-HCl and allopurinol. As we add more studies to our database, it is likely that more SST-upregulating compounds will be noted.

Note 2/21/2022: Another observation is that SST is strongly differently altered at varying time points in stem cell differentiation. For example, it's the single most strongly upregulated gene in a comparison of mouse stem cells differentiating to pancreas cells at day 15 vs day 8 (PMID 22278131). Here, SST isn't necessarily a key effector of Alzheimer's, but it is found in a swarm of genes relevant to stemness. A number of our posts focus on the relationship between Alzheimer's and stem cells/stemness.

Unlike SST, SVOP has received little mention with respect to Alzheimer’s. We don’t find any brain-specific studies wherein a drug upregulated SVOP, but we do note that hydroxyurea, a compound proposed to alleviate the effects of Alzheimer’s (Hydroxyurea attenuates oxidative, metabolic, and excitotoxic stress in rat hippocampal neurons and improves spatial memory in a mouse model of Alzheimer’s disease), upregulated SVOP in mouse embryos (PMID 27208086).

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