The wiring diagram of the brain takes another hit

Is there anything duller than wire? It conducts electricity. That’s about it. Copper wires conduct better than Aluminum wires. So what.  End of story. 

That’s pretty much the way we thought of axons, the wires of the nervous system. Thicker axons conduct faster than thin ones, and insulated axons conduct faster than non-insulated ones. The insulation is made out of fat and called myelin.  Just as fat in meat looks white, a bunch of axons sheathed by myelin looks white, which is how white matter got its name. 

Those of you old enough to remember vinyl records, know just how different a record sounds when played at the wrong speed.  That’s what an MS patient has to deal with.  The disease attacks white matter mostly, which means that when myelin is lost or damaged, nerve impulses slow down.  Information gets through, but it’s garbled. 

So we knew that losing myelin causes trouble, but other than that, it was assumed that myelin, once laid down by the cell producing it (the oligodendrocyte) was stable unless trauma or disease damaged it. 

That was until adaptive myelination came along roughly 10 years ago.  There is an excellent review [ Neuron vol. 109 pp. 1258 – 1273 ’21 ] which is irritating to read if you are looking for solid experimental facts.  This is not the fault of the authors.  They are trying to picture the frontier of a fast moving field.  By nature there is a lot of speculation in such an article, which would be a lot shorter (and duller) without it.  

However the following words occur frequently — could (43), has been understood (3), suggested (6), would (12), may (39) and is thought to (2).

The cells making the myelin are just that: cells.  Since the myelin they make is confined within them, a myelinated axon looks like a string of hot dogs, each dog the province of one oligo.  The space between the hot dogs is called the node (of Ranvier), and this is why myelinated axons conduct faster.  The impulse jumps between the nodes (saltatory conduction). 

Adaptive myelination comes in when you stimulate an axon — the myelin gets thicker, meaning that it conducts faster.   Also neuronal activity is held to alter myelin (the space between nodes gets longer meaning they conduct faster). 

Not all axons are myelinated, and activity ‘is thought to’ increase myelination of them. 

This has extremely profound consequences for how we think the brain works.  At the end of the post you’ll find an older one arguing that a wiring diagram of the brain (how the neurons are connected to each other) is far from enough to understand the brain.  But the article assumes that the wires are pretty much fixed in how they act. The Neuron article shows that this is wrong.  

Imagine if the connections between transistors on a computer chip, grew and shrunk depending on how much current flowed through them.   That appears to be the case for the brain.

Here’s the old post

Would a wiring diagram of the brain help you understand it?

Every budding chemist sits through a statistical mechanics course, in which the insanity and inutility of knowing the position and velocity of each and every of the 10^23 molecules of a mole or so of gas in a container is brought home.  Instead we need to know the average energy of the molecules and the volume they are confined in, to get the pressure and the temperature.

However, people are taking the first approach in an attempt to understand the brain.  They want a ‘wiring diagram’ of the brain. e. g. a list of every neuron and for each neuron a list of the other neurons connected to it, and a third list for each neuron of the neurons it is connected to.  For the non-neuroscientist — the connections are called synapses, and they essentially communicate in one direction only (true to a first approximation but no further as there is strong evidence that communication goes both ways, with one of the ‘other way’ transmitters being endogenous marihuana).  This is why you need the second and third lists.

Clearly a monumental undertaking and one which grows more monumental with the passage of time.  Starting out in the 60s, it was estimated that we had about a billion neurons (no one could possibly count each of them).  This is where the neurological urban myth of the loss of 10,000 neurons each day came from.  For details see https://luysii.wordpress.com/2011/03/13/neurological-urban-legends/.

The latest estimate [ Science vol. 331 p. 708 ’11 ] is that we have 80 billion neurons connected to each other by 150 trillion synapses.  Well, that’s not a mole of synapses but it is a nanoMole of them. People are nonetheless trying to see which areas of the brain are connected to each other to at least get a schematic diagram.

Even if you had the complete wiring diagram, nobody’s brain is strong enough to comprehend it.  I strongly recommend looking at the pictures found in Nature vol. 471 pp. 177 – 182 ’11 to get a sense of the  complexity of the interconnection between neurons and just how many there are.  Figure 2 (p. 179) is particularly revealing showing a 3 dimensional reconstruction using the high resolutions obtainable by the electron microscope.  Stare at figure 2.f. a while and try to figure out what’s going on.  It’s both amazing and humbling.

But even assuming that someone or something could, you still wouldn’t have enough information to figure out how the brain is doing what it clearly is doing.  There are at least 3 reasons.

l. Synapses, to a first approximation, are excitatory (turn on the neuron to which they are attached, making it fire an impulse) or inhibitory (preventing the neuron to which they are attached from firing in response to impulses from other synapses).  A wiring diagram alone won’t tell you this.

2. When I was starting out, the following statement would have seemed impossible.  It is now possible to watch synapses in the living brain of awake animal for extended periods of time.  But we now know that synapses come and go in the brain.  The various papers don’t all agree on just what fraction of synapses last more than a few months, but it’s early times.  Here are a few references [ Neuron vol. 69 pp. 1039 – 1041 ’11, ibid vol. 49 pp. 780 – 783, 877 – 887 ’06 ].  So the wiring diagram would have to be updated constantly.

3. Not all communication between neurons occurs at synapses.  Certain neurotransmitters are generally released into the higher brain elements (cerebral cortex) where they bathe neurons and affecting their activity without any synapses for them (it’s called volume neurotransmission)  Their importance in psychiatry and drug addiction is unparalleled.  Examples of such volume transmitters include serotonin, dopamine and norepinephrine.  Drugs of abuse affecting their action include cocaine, amphetamine.  Drugs treating psychiatric disease affecting them include the antipsychotics, the antidepressants and probably the antimanics.

Statistical mechanics works because one molecule is pretty much like another. This certainly isn’t true for neurons. Have a look at http://faculties.sbu.ac.ir/~rajabi/Histo-labo-photos_files/kora-b-p-03-l.jpg.  This is of the cerebral cortex — neurons are fairly creepy looking things, and no two shown are carbon copies.

The mere existence of 80 billion neurons and their 150 trillion connections (if the numbers are in fact correct) poses a series of puzzles.  There is simply no way that the 3.2 billion nucleotides of out genome can code for each and every neuron, each and every synapse.  The construction of the brain from the fertilized egg must be in some sense statistical.  Remarkable that it happens at all.  Embryologists are intensively working on how this happens — thousands of papers on the subject appear each year.

 

 

A clever way to attack autoimmune disease

The more we study the immune system, the more complicated it becomes.  Take multiple sclerosis.  A recent study looked at just about every immune parameter in blood they could think of in a collection of 42 monozyotic (identical) twins, one of whom had MS, the other didn’t.  They came up with nothing [ Proc. Natl. Acad. Sci. vol. 117 pp. 21546  – 21556 ’20 ].

Classification of anything (particularly diseases) is always a battle between the lumpers and the splitters.  The initial split in the immune system came between B cells and T cells.  The letters have nothing to do with their function, but rather where they were first found (Bursa of Fabricius, Thymus).

B cells are lymphocytes which secrete immunoglobulin antibodies.  Malignancies of them account for 90 – 95% of leukemias and lymphomas.

T cells are involved in the recognition of antigens.  They can stimulate (or repress) B cells.  Others are used to kill other cells. There are 2,000,000,000,000 of them in our bodies, making them comparable in mass to the brain.

T cells have been subdivided in to helper T cells (which Express the  Cd4 antigen ) and cytotoxic/suppressor cells which express the antigen CD8. Splitting didn’t stop there.  There are two types of helper T cells (Th1 and Th2), but the new kid on the block is the Th17 cell, which Janus-like provide protection from bacterial and fungal infections at mucosal surfaces (e.g. gut, bladder) but which can also induce autoimmune disease.

How to stop the second without causing death from infection. A very clever way was found in Cell vol. 182 pp. 641 – 654 ’20.  Areas of inflammation usually have low oxygen.  Bacteria and Archaea from which we are descended did just fine without oxygen, using something called glycolysis to burn glucose without it, so deep within our cells is the ability to use it when the going gets tough (e.g. hypoxic)

What the authors did was knock out one enzyme involved in glycolysis (Glucose phosphate isomerase — aka Gpi1) — which changes glucose 6 phosphate to fructose 6 phosphate.   This kills Th17 cells living in hypoxia.  What about the good Th17 cells protecting us? They can use a pathway I’d long forgotten about the pentose phosphate shunt and oxidative phosphorylation.

Well did it work?  Actually it did in an animal model of multiple sclerosis called EAE.  It was harder to induce when Gpi1 was knocked down, but the animals didn’t get a bunch of infections, if the protective role of Th17 cells had been lost.

Two disconcerting papers

We all know that mutations cause cancer and that MRI lesions cause disability in multiple sclerosis. We do, don’t we? Maybe we don’t, say two papers out this October.

First: cancer. The number of mutations in stem cells from 3 organs (liver, colon, small intestine) was determined in biopsy samples from 19 people ranging in age 3 to 87 [ Nature vol. 538 pp. 260 – 264 ’16 ].th How did they get stem cells? An in vitro system was sued to expand single stem cells into epithelial organoids, and then the whole genome was sequenced of each. Some 45 organoids were used. Some 79,790 heterozygous clonal mutations were found. They then plotted the number of mutations vs. the age of the patient. When you have a spread in patient ages (which they did) you can calculate a tissue mutation rate for its stem cells. What is remarkable, is that all 3 tissues had the same mutation rate — about 40 mutations per year. Not bad. That’s only 4,000 if you live to 100 in your 3.2 BILLION nucleotide genome.

This is so  remarkable because the incidence of cancer is wildly different in the 3 tissues, so if mutations occurring randomly cause cancer, all 3 tissues should have the same cancer incidence (and there is much less liver cancer than gut cancer).

Of course there’s a hooker. The numbers are quite small, only 9 organoids from liver with a relatively small age range spanning only 25 years. There were more organoids from colon and small and the age ranges was wider but, clearly, the work needs o be replicated with a lot more samples. However, a look at figure one shows that the slope of the plot of mutation number vs. age is quite similar.

Second: Multiple sclerosis. First, some ancient history. I started in neurology before there were CAT scans and MRIs. All we had to evaluate the MS patient was the neurologic exam. So we’d see if new neurologic signs had developed, or the old ones worsened. There were all sorts of clinical staging scores and indices. Not terribly objective, but at least they measured function which is what physician and patient cared about the most.

The MRI revolutionized both diagnosis and our understanding of MS. We quickly found that even when the exam remained constant, that new lesions appeared and disappeared on the MRI totally silent to both patient and physician. I used to say that prior to MRI neurologists managed patients the way a hematologist would manage leukemics without blood counts, by looking at them to see how pale they were.

In general the more lesions that remained fixed, the worse shape the patient was in. So new drugs against MS could easily be evaluated without waiting years for the clinical exam to change, if a given drug just stopped lesions from appearing — stability was assumed to ensue (or at least it was when I retired almost exactly 4 presidential elections ago).

Enter Laquinimod [ Proc. Natl. Acad. Sci. vol. 113 pp. E6145 – E6152 ’16 ] which has a much greater beneficial effect on disability progression (e.g. less) than it does on clinical relapse rate (also less) and lesion appearance rate on MRI (also less). So again there is a dissociation between the MRI findings and the patient’s clinical status. Here are references to relevant papers — which I’ve not read —
Comi G, et al.; ALLEGRO Study Group (2012) Placebo-controlled trial of oral laquini- mod for multiple sclerosis. N Engl J Med 366(11):1000–1009.

Filippi M, et al.; ALLEGRO Study Group (2014) Placebo-controlled trial of oral laqui- nimod in multiple sclerosis: MRI evidence of an effect on brain tissue damage. J Neurol Neurosurg Psychiatry 85(8):851–858.

Vollmer TL, et al.; BRAVO Study Group (2014) A randomized placebo-controlled phase III trial of oral laquinimod for multiple sclerosis. J Neurol 261(4):773–783.

It is well known that there are different kinds of lesions in MS (some destroying axons, others just stripping off their myelin). Since I’ve left the field, I don’t know if MRI can distinguish the two types, and whether this was looked at.

The disconcerting thing about this paper, is that we may have given up on drugs which would  clinically help patients (rather than a biological marker) because they didn’t help the MRI ! ! !

Is a rational treatment for Multiple Sclerosis in our future?

Two very recent papers taken together point the way to a rational treatment of multiple sclerosis (and probably all autoimmune disease). The short story:
Paper #1 found a way to find the antigen or antigens patients with MS are reacting to
Paper #2 found a way to selectively impair the response to an inciting antigen without clobbering the whole immune system

Some history: Some evening in 1966 or 1967 a fellow neurology resident and I were sitting on the ward having dealt with the complications of high doses corticosteroids for a case of optic neuritis (often the first sign of MS). I said, some day they’ll look at what we’re doing the way we look at docs of 200 years ago using leeches (and bloodletting). As a kid, I remember my parents driving into Philly. Shortly after getting over the Ben Franklin bridge we’d pass a pharmacy offering leeches on its sign.

It was obvious even back then that MS in some way was an attack by the immune system on the brain. Finding the particular antigen the system was reacting to would lead us to the cause and hopefully less simplistic treatment than clobbering the immune system. We didn’t know all the proteins we had or even how many, so people would look for antibodies to a variety causes (which they’d arrived at by reasoning, not data). Increased antibody titers to a variety of viruses were found, but that led nowhere. No one ever isolated a virus from MS brain, although sightings on electron microscopy were eagerly reported. Eventually it became obvious that the immune system was on high alert with increased antibodies to lots of things.

This leads to paper #1 [ Proc. Natl. Acad. Sci. vol. 113 pp. 2188 – 2193 ’16 ] To make a long story short they used something called the Human Protein Atlas Program to find what proteins the antibodies in MS patients were reacting to. So rather than having a theory about what MS patients might be reacting to and testing it, they looked at all proteins and watched. It’s the difference between being a Greek philosopher reasoning things out from first principles and collecting data. Only when the technology is available can you stop a priori theorizing and just look. Don’t be too hard on the earlier researchers, they didn’t have the tools.

The found that MS patients were reacting to a protein called anoctamin2, which actually showed increased expression near and inside the demyelinating plaques of MS.

For the gory details keep reading, otherwise skip to **** where I’ll discuss paper #2

Gory details — The Human Protein Atlas produces human protein fragments, selected on the basis of their low similarity to other proteins in the proteome. [ Science vol. 347 1260419 (23 Jan) ’15 ] The atlas hopes to find out where and how much of each our proteins is at the tissue and cellular level. It is based on antibody based profiling on tissue microarrays (of proteins?). This based on transcript expression (RNA-Seq), and immunohistochemistry (24,028 antibodies coresponding to 16,975 protein coding genes). 44 tissues were studied. The antibodies produced more than 13 million tissue based mmunohistochemistry images. They also report subproteomes (secreted proteins n = 3,171, and membrane bound proteins n = 5,570). Interstingly there was an overall concurrence between mRNA and protein levels for a given gene product across various tissues.

The PNAS paper profiled 2,169 plasma samples from MS cases and population based controls (with neurologic disease) using bead arrays built with 384 human protein fragments seleted from an initial screening with 11,520 antigens. There was increased reactivity to anoctamin2 (aka TMEM16B) in MS vs. controls (by how much?). This was corroborated in independent assay with alternative protein constructs and by epitope mapping with peptides covering the identified region of anoctamin 2.

ImmunoFLuorescence in human MS brain tissue showed increased anoctamin2 expression as small cellular aggregates near and inside MS lesions. The controls had other neurologic disease. There was a 5.3 fold change in fluorescence intensity in the MS group. The antibodies are directed against the amino terminal region.

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Paper #2 — [ Nature vol. 530 pp. 422 – 423, 434 – 440 ’16 ] basically found a way to knock out the immune system’s response to a single antigen — not all of them. The point is that just an antigen by itself isn’t enough to turn the immune system on. A costimulatory molecule must also be present on the antigen presenting cell. If it isn’t there the immune system is actually turned off by forming regulatory T cells (which even though they are part of the immune system they actually turn it off).

One can form models of human autoimmune disease in mice. Two such are EAE (Experimental Allergic Encephalomyelitis) formed by giving the animal myelin basic protein (a constituent of myelin which is attacked in MS), and rheumatoid arthritis (formed by giving collagen to the animals). What is so great about this paper is that MHC II carrying peptides from collagen suppress disease in a mouse model of rheumatoid arthritis, but NOT in mice with EAE. MHC-II carrying CNS antigen peptides control EAE but not collagen induced arthritis.. In addition neither treatment impaired the immune response to infection — something that almost always happens when you clobber the immune system.

Well it’s a long way from the lab to the bedside, but imagine finding what the immune system is reacting to and stopping it (without stopping the immune system). That’s what these two papers portend. Exciting times.