Watch this space

I know far more about head trauma than any neurologist should. For three and a half years I worked with two active neurosurgeons covering a huge area of an eastern state. Our drawing radius ranged from 35 to 125 miles depending on direction. I was on first call every other night and weekend, and covered all the patients (including the neurosurgical ones) during those times. It’s amazing what you’ll do to get your kids through college. I was the first to see any head trauma cases that came in whether our service admitted them or not (multiple trauma cases usually went to general surgery and/or orthopedics, with out group following them as consultants).

So it’s time to talk about orbital (eye socket) fractures. This has great relevance for the case against Darren Wilson, the cop who killed Michael Brown. As far as I can tell, whether Wilson did or not sustain an orbital fracture is extremely controversial, with statements and denials all over the internet (most of them 5 -6 days old).

The truth of the matter will be very easy to establish once his X-rays (and CAT scans) are available. If Wilson sustained any head trauma at all, it is inconceivable to me that he didn’t have X-rays and CAT scans out the gazoo (technical term).

Some orbital fractures are very easy to see with a CAT scan, which shows bone beautifully. The orbit is adjacent to sinuses (air filled spaces) below and toward the nose. Fractures bleed. Normally the sinuses are filled with air which doesn’t stop X-rays, so they normally look black. Bone stops X-rays so they look white on CAT scan. Blood (or mucus) is very easy to see in a sinus on a CAT scan.

There is always a question about how old a fracture is, but if blood is found in a sinus adjacent to the fracture, you can conclude that the fracture is new.

Sometimes there is a sinus (the frontal sinus) above the orbit, but not always. The side of the orbit toward the ear is just bone.

So the data is out there somewhere. Watch this space for more interpretation should Wilson actually have sustained one.

The only other data available for all to see, are the convenience store videos, which show how Brown was acting shortly before he was killed. It isn’t pretty. I’m sure there are better links to it, so ignore the right wing chatter, and just look at the data. http://www.breitbart.com/Big-Government/2014/08/18/Michael-Brown-Allegedly-Bum-Rushed-Officer-Punched-Him-in-Face-Grabbed-Gun-Taunted-Him

Brown was big (reportedly 6′ 4” and 300 pounds), and the video shows him pushing a clerk who doesn’t even come up to his shoulder, when the clerk (who also appears to be a person of color) confronts him.

Tolstoy rides again — Schizophrenia

“A field plagued by inconsistency, and perhaps even a degree of charlatanism” — strong stuff indeed [ Neuron vol. 83 pp. 760 - 763 '14 ]. They are talking about studies attempting to find the genetic causes of schizophrenia.

This was the state of play four and a half years ago (in a post of April 2010)

Happy families are all alike.; every unhappy family is unhappy in its own way”. Thus beginneth Anna Karenina. That wasn’t supposed to happen with hereditary disease. The examples we had before large scale DNA sequencing became cheap were basically one gene causing one disease. Two of the best known cases were sickle cell anemia and cystic fibrosis. In the former, a change in a single position (nucleotide) of DNA caused a switch of one amino acid (valine for glutamic) acid at position #6 in beta hemoglobin. In the latter, all mutations have been found in a single gene called CFTR. 85% of known mutations involve the loss of 1 amino acids. But by 2003 over 600 different mutations accounted for only part of the other 15%. There is plenty of room for mutation as CFTR has 1480 amino acids. The kids I took care of in the muscular dystrophy clinic all turned out to have mutations in the genes for proteins found in muscle.

Why not look for the gene causing schizophrenia? It’s a terrible disease (the post “What is Schizophrenia really Like?” is included after the **** ) with a strong hereditary component. There was an awful era in psychiatry when it was thought to be environmental (e.g. the family was blamed). Deciding what is hereditary and what is environmental can be tricky. TB was thought to be hereditary (for a time) because it also ran in families. So why couldn’t schizophrenia be environmental? Well, if you are an identical twin and the other twin has it, your chances of having schizophrenia are 45%. If you are a fraternal twin your chance of having it are 3 times less (15%). This couldn’t be due to the environment.

It’s time to speak of SNPs (single nucleotide polymorphisms). Our genome has 3.2 gigaBases of DNA. With sequencing being what it is, each position has a standard nucleotide at each position (one of A, T, G, or C). If 5% of the population have one of the other 3 at this position you have a SNP. By 2004 some 7 MILLION SNPs had been found and mapped to the human genome. So to find ‘the gene’ for schizophrenia, just take schizophrenics as a group (there are lots of them — about 1% of the population) look at their SNPs, and see if they have any SNPs in common.

Study after study found suspect SNPs (which can be localized exactly in the genome) for schizophrenia. The area of the genome containing the SNP was then searched for protein coding genes to find the cause of the disease. Unfortunately each study implicated a different bunch of SNPs (in different areas of the genome). A study of 750 schizophrenics and an equal number of controls from North Carolina used 500,000 SNPs. None of the previous candidate genes held up. Not a single one [ Nature vol. 454 pp., 154 - 157 '08 ]

As of 2009 here are 3,000 diseases showing simple inheritance in which a causative gene hasn’t been found. This is the ‘dark matter’ of the genome. We are sure it exists (because the diseases are hereditary) but we simply can’t see it.

There is presently a large (and expensive) industry called GWAS (Genome Wide Association Studies) which uses SNPs to look for genetic causes of diseases with a known hereditary component. One study on coronary heart disease had 23,000 participants. In 2007 the Wellcome Trust committed 45 million (pounds? dollars?) for studies of 27 diseases in 120,000 people. This is big time science. GWAS studies have found areas of the genome associated with various disorders. However, in all GWAS studies so far, what they’ve picked up explains less than 5% of the heritability. An example is height (not a disease). Its heritability is 80% yet the top 20 candidate genetic variants identified explain only 3% of the variance. People have called for larger and larger samples to improve matters.

What’s going on?

It’s time for you to read “Genetic Heterogeneity in Human Disease” [ Cell vol. 141 pp. 210 - 217 '10 ]. It may destroy GWAS. Basically, they argue that most SNPs are irrelevant, don’t produce any functional change, and have arisen by random mutation. They are evolutionary chaff if you will. A 12 year followup study of 19,000 women looked at the 101 SNPs found by GWAS as risk variants for cardiovascular disease — not one of them predicted outcome [ J. Am. Med. Assoc. vol. 303 pp. 631 - 637 '10 ]. The SNPs haven’t been eliminated by natural selection, because they aren’t causing trouble and because the human population has grown exponentially.

There’s a lot more in this article, which is worth reading carefully. It looks like what we’re calling a given disease with a known hereditary component (schizophrenia for example) is the result of a large number of different (and rather rare) mutations. A given SNP study may pick up one or two rare mutations, but they won’t be found in the next. It certainly has been disheartening to follow this literature over the years, in the hopes that the cause of disease X, Y or Z would finally be found, and that we would have a logical point of attack (but see an old post titled “Some Humility is in Order”).

Is there an analogy?

200 years ago (before Pasteur) physicians classified a variety of diseases called fevers. They knew they were somewhat different from each other (quotidian fever, puerperal fever, etc. etc.). But fever was the common denominator and clinically they looked pretty much the same (just as dogs look pretty much the same). Now we know that infectious fever has hundreds of different causes. The Cell article argues that, given what GWAS has turned up so far, this is likely to be the case for many hereditary disorders.

Tolstoy was right.

Fast forward to the present [ Nature vol. 511 pp. 412 - 413, 421 - 427 '14 ] This is a paper from the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC) which analyzed some 36,989 and 113,075 controls. They found 128 independent associations spanning 108 conservatively defined loci, meeting genome-wide significance. 83/128 hadn’t been previously reported. The associations were enriched among genes expressed in brain. Prior to this work, some 30 schizophrenia associated loci had been found through genome wide association studies (GWAS).

Interestingly 3/4 of the 108 loci include protein coding genes (of which 40% represent a single gene and another 8% are within 20 kiloBases of a gene).

The editorial noted that there have been 800 associations ‘of dubious value’

The present risk variants are common, and contribute in most (if not all) cases. One such association is with the D2 dopamine receptor, but not with COMT (which metabolizes dopamine). The most significant association is within the major histocompatibility complex (MHC).

The paper in Neuron cited above notes that schizophrenia genetics is a “field plagued by inconsistency, and perhaps even a degree of charlatanism” and that that there have been 800 associations ‘of dubious value’. The statistical sins of earlier work are described resulting in many HUNDREDS of variant associations with schizophrenia, and scores of falsely implicated genes. Standards have been developed to eliminate them [ Nat. Rev. Genet. vol. 9 pp. 356 - 369 '08 ].

Here is their description of the statistical sins prior to GWAS “Before GWAS, the standard practice for investigating schizophrenia genetics (as well as many other areas) was to pick a candidate gene (usually based on dopamine or glutamate pathways or linkage studies) and compare the frequency of genetic variants in cases and controls. Any difference with a p value 0.05) p values, and associations seen in partitions of a data set. Beyond all of these obvious statistical transgressions, these studies often entirely ignored well-established causes of spurious associations such as population stratification. Labs would churn out separate papers for gene after gene with no correction for multiple testing, and, on top of all of that, there was a publication bias against negative findings. “

There is a hockey stick model in which few real associations aren’t found until a particular sample size is breached. This works for hypertension.

GWAS identifies genomic regions, not precise risk factors. It is estimated the the 108 loci implicate 350 genes. However the Major Histocompatibility Complex (MHC) counts as one locus and it has tones of genes.

The NHGRI website tracks independent GWAS signals for common diseases and traits, and currently records 7,300 associations with a p value under 5 * 10^-8. Only 20 have been tracked to causal variants (depending on criteria.

The number of genes implicated will only grow as the PGC continues to increase the sample size to capture smaller and smaller effect sizes — how long will it be until the whole genome is involved? There are some significant philosophical issues involved, but this post is long enough already.

*****
What Schizophrenia is really Like

I feel that writing to you there I am writing to the source of a ray of light from within a pit of semi-darkness. It is a strange place where you live, where administration is heaped upon administration, and all tremble with fear or abhorrence (in spite of pious phrases) at symptoms of actual non-local thinking. Up the river, slightly better, but still very strange in a certain area with which we are both familiar. And yet, to see this strangeness, the viewer must be strange.”

“I observed the local Romans show a considerable interest in getting into telephone booths and talking on the telephone and one of their favorite words was pronto. So it’s like ping-pong, pinging back again the bell pinged to me.”

Could you paraphrase this? Neither can I, and when, as a neurologist I had occasion to see schizophrenics, the only way to capture their speech was to transcribe it verbatim. It can’t be paraphrased, because it makes no sense, even though it’s reasonably gramatical.

What is a neurologist doing seeing schizophrenics? That’s for shrinks isn’t it? Sometimes in the early stages, the symptoms suggest something neurological. Epilepsy for example. One lady with funny spells was sent to me with her husband. Family history is important in just about all neurological disorders, particularly epilepsy. I asked if anyone in her family had epilepsy. She thought her nephew might have it. Her husband looked puzzled and asked her why. She said she thought so because they had the same birthday.

It’s time for a little history. The board which certifies neurologists, is called the American Board of Psychiatry and Neurology. This is not an accident as the two fields are joined at the hip. Freud himself started out as a neurologist, wrote papers on cerebral palsy, and studied with a great neurologist of the time, Charcot at la Salpetriere in Paris. 6 months of my 3 year residency were spent in Psychiatry, just as psychiatrists spend time learning neurology (and are tested on it when they take their Boards).

Once a month, a psychiatrist friend and I would go to lunch, discussing cases that were neither psychiatric nor neurologic but a mixture of both. We never lacked for new material.

Mental illness is scary as hell. Society deals with it the same way that kids deal with their fears, by romanticizing it, making it somehow more human and less horrible in the process. My kids were always talking about good monsters and bad monsters when they were little. Look at Sesame street. There are some fairly horrible looking characters on it which turn out actually to be pretty nice. Adults have books like “One flew over the Cuckoo’s nest” etc. etc.

The first quote above is from a letter John Nash wrote to Norbert Weiner in 1959. All this, and much much more, can be found in “A Beatiful Mind” by Sylvia Nasar. It is absolutely the best description of schizophrenia I’ve ever come across. No, I haven’t seen the movie, but there’s no way it can be more accurate than the book.

Unfortunately, the book is about a mathematician, which immediately turns off 95% of the populace. But that is exactly its strength. Nash became ill much later than most schizophrenics — around 30 when he had already done great work. So people saved what he wrote, and could describe what went on decades later. Even better, the mathematicians had no theoretical axe to grind (Freudian or otherwise). So there’s no ego, id, superego or penis envy in the book, just page after page of description from well over 100 people interviewed for the book, who just talked about what they saw. The description of Nash at his sickest covers 120 pages or so in the middle of the book. It’s extremely depressing reading, but you’ll never find a better description of what schizophrenia is actually like — e.g. (p. 242) She recalled that “he kept shifting from station to station. We thought he was just being pesky. But he thought that they were broadcasting messages to him. The things he did were mad, but we didn’t really know it.”

Because of his previous mathematical achievments, people saved what he wrote — the second quote above being from a letter written in 1971 and kept by the recipient for decades, the first quote from a letter written in 12 years before that.

There are a few heartening aspects of the book. His wife Alicia is a true saint, and stood by him and tried to help as best she could. The mathematicians also come off very well, in their attempts to shelter him and to get him treatment (they even took up a collection for this at one point).

I was also very pleased to see rather sympathetic portraits of the docs who took care of him. No 20/20 hindsight is to be found. They are described as doing the best for him that they could given the limited knowledge (and therapies) of the time. This is the way medicine has been and always will be practiced — we never really know enough about the diseases we’re treating, and the therapies are almost never optimal. We just try to do our best with what we know and what we have.

I actually ran into Nash shortly after the book came out. The Princeton University Store had a fabulous collection of math books back then — several hundred at least, most of them over $50, so it was a great place to browse, which I did whenever I was in the area. Afterwards, I stopped in a coffee shop in Nassau Square and there he was, carrying a large disheveled bunch of papers with what appeared to be scribbling on them. I couldn’t bring myself to speak to him. He had the eyes of a hunted animal.

The climate gods have a sardonic sense of humor

Things haven’t been going too well for Global Warming. First, there has been essentially no change in global mean temperature for 14 – 17 years (depending on which of 4 measures you use). So Global Warming was rebranded as Climate Change. Then, we’ve been told that climate change would lead to more and more ‘extreme weather events’ (translation hurricanes, tornadoes etc. etc.) So in one of the coolest New England summers within memory and with nearly half of the 6 month hurricane season gone, we have a very quiet, not to say comatose, hurricane season.

At the onset of the 2014 season NOAA (National Oceanic and Atmospheric Administration) predicted a 70% chance of a below average season. The numbers they expected were

8 – 13 Named storms (top winds over 39 mph — not very impressive)

3 – 6 Hurricanes (top winds over 74 mph)

1 – 2 Category 3 storms (sustained winds over 110 mph)

This was updated 7 August to a 70% probability of an even less exciting season

7 – 12 Named storms (top winds over 39 mph — not very impressive)

3 – 6 Hurricanes (top winds over 74 mph)

0 – 2 Category 3 storms (sustained winds over 110 mph)

So instead of extreme weather events, we have extremely boring (but pleasant) weather and just 2 named storms which turned into hurricanes. No category 3 events, and as of this writing, the Atlantic is extremely quiet. This has been blamed on dry air from Africa and (amazingly enough) unusually cool water temperatures in the Atlantic. Recall that it has been argued that the stability of global temperature over the past decade is due to heat going into the deep ocean where we can’t see it.

To be noted if you look at the graph in http://www.accuweather.com/en/weather-news/atlantic-tropical-threat-possible-gulf-coast/32555368, which is of hurricane frequency vs. date, and try to mentally integrate the area under the curve in your head, that only about 20% of the hurricanes have occurred by this time. Peak frequency is 2 weeks from now (11 September) and the frequency of 20 August is half maximal.

Would anyone like to guess when (not if) this will be blamed on Global Warming/Climate Change? I’d be very surprised if it weren’t, and if it is, remember that a theory which can explain anything explains nothing.

Bad news on the cancer front

[ Nature vol. 512 pp. 143 - 144, 155 - 160 '14 ] Nuc-seq is an innovative sequencing method which achieves almost complete sequencing of whole genomes in single cells. It sequences DNA from cells about to divide (the G2/M stage of the cell cycle which has twice the DNA content of the usual cell). Genomes of multiple single cells from two types of human breast cancer (estrogen receptor positive and triple negative — the latter much more aggressive) and found that no two genomes of individual tumor cells were identical. Many cells had new mutations unique to them.

This brings into question what we actually mean by a cancer cell clone. They validated some of the single cell mutations by deep sequencing of a single molecule (not really sure what this is).

Large scale structural changes in DNA (amplification and deletion of large blocks of DNA) occurred early in tumor development. THey remain stable as clonal expansion of the tumor occur (e.g. they were found in all the cancer cells whose genome was sequenced). Point mutations accumulated more gradually generating extensive subclonal diversity. Many of the mutations occur in less than 10% of the tumor mass. Triple negative breast cancers (aggressive) have mutation rates 13 times greater than the slower growing estrogen receptor positive breast cancer cells.

This implies that the mutations are there BEFORE chemotherapy. This has always been a question as most types of chemotherapy attack DNA replication and are inherently mutagenic. It also implies that slamming cancer with chemotherapy early before it has extensively mutated is locking the barn door after the horse has been stolen. It still might help in preventing metastasis, so the approach remains viable.

However nuc-seq may only be useful for cancer cells without aneuploidy http://en.wikipedia.org/wiki/Aneuploidy which is extremely common in cancer cells.

Why is this such bad news? It means that before chemotherapy even starts there is a high degree of genetic diversity present in the tumor cell population. This means that natural selection (in the form of chemotherapy) has a diverse population to work on at the get go, making resistance far more likely to occur.

Had enough? Here’s more — [ Nature vol. 511 pp. 543 - 550 '14 ] A report of 230 resected lung adenocarcinomas using mRNA, microRNA and DNA sequencing found an incredible 8.8 mutations/megaBase — e.g. 3.2 * 3.8 * 1,000 == 28,000 mutations. Aberrations in NF1, MET. ERBB2 and RIT1 occured in 13% and were enriched in samples otherwise lacking an activated oncogene. Even when not mutated, mRNA splicing was different in tumors. As far as oncogenic pathways, multiple pathways were involved — p53in 63%, PI3K mTOR in 25%, Receptor Tyrosine Kinase in 76%, cell cycle regulators 64%.

This is the opposite side of the coin from the first paper, where the genomes of single tumor cells were sequenced. It is doubtful that all cells have the 28,000 mutations, which probably result from each cell having a subset. The first paper didn’t count how many mutations a single cell had (as far as i could see).

So oncologists are attacking a hydra-headed monster.

Are Van der Waals interactions holding asteroids together?

A recent post of Derek’s concerned the very weak (high kD) but very important interactions of proteins within our cells. http://pipeline.corante.com/archives/2014/08/14/proteins_grazing_against_proteins.phpAr

Most of this interaction is due to Van der Waals forces — http://en.wikipedia.org/wiki/Van_der_Waals_force. Shape shape complementarity (e.g. steric factors) and dipole dipole interactions are also important.

Although important, Van der Waals interactions have always seemed like a lot of hand waving to me.

Well guess what, they are now hypothesized to be what is holding an asteroid together. Why are people interested in asteroids in the first place? [ Science vol. 338 p. 1521 '12 ] “Asteroids and comets .. reflect the original chemical makeup of the solar system when it formed roughly 4.5 billion years ago.”

[ Nature vol. 512 p. 118 '14 ] The Rosetta spacecraft reached the comet 67P/Churyumov-Gerasimenko after a 10 year journey becoming the first spacecraft to rendezvous with a comet. It will take a lap around the sun with the comet and will watch as the comet heats up and releases ice in a halo of gas and dust. It is now flying triangles in front of the comet, staying 100 kiloMeters away. In a few weeks it will settle into a 30 kiloMeter orbit around he comet. It will attempt to place a lander (Philae) the size of a washing machine on its surface in November. The comet is 4 kiloMeters long.

[ Nature vol. 512 pp. 139 - 140, 174 - 176 '14 ] A kiloMeter sized near Earth asteroid called (29075) 1950 DA (how did they get this name?) is covered with sandy regolith (heterogeneous material covering solid rock { on earth } it includes dust, soil, broken rock ). The asteroid rotates every 2+ hours, and it is so small that gravity alone can’t hold the regolith to its surface. An astronaut could scoop up a sample from its surface, but would have to hold on to the asteroid to avoid being flung off by the rotation. So the asteroid must have some degree of cohesive strength. The strength required is 64 pascals to hold the rubble together — about the pressure that a penny exerts on the palm of your hand. A Pascal is 1/101,325 of atmospheric pressure.

They think the strength comes from van der Waals interactions between small (1 – 10 micron) grains — making it fairy dust. It’s rather unsatisfying as no one has seen these particles.

The ultimate understanding of the large multi-protein and RNA machines (ribosome, spliceosome, RNA polymerase etc. etc. ) without which life would be impossible will involve the very weak interactions which hold them together. Along with permanent dipole dipole interactions, charge interactions and steric complementarity, the van der Waals interaction is high on anyone’s list.

Some include dipole dipole interactions as a type of van der Waals interaction. The really fascinating interaction is the London dispersion force. These are attractions seen between transient induced dipoles formed in the electron clouds surrounding each atomic nucleus.

It’s time to attempt the surmount the schizophrenia which comes from trying to see how quantum mechanics gives rise to the macroscopic interactions between molecules which our minds naturally bring to matters molecular (with a fair degree of success).

Steric interactions come to mind first — it’s clear that an electron cloud surrounding molecule 1 should repel another electron cloud surrounding molecule 2. Shape complementarity should allow two molecules to get closer to each other.

What about the London dispersion forces, which are where most of the van der Waals interaction is thought to be. We all know that quantum mechanical molecular orbitals are static distributions of electron probability. They don’t fluctuate (at least the ones I’ve read about). If something is ‘transiently inducing a dipole’ in a molecule, it must be changing the energy level of a molecule, somehow. All dipoles involve separation of charge, and this always requires energy. Where does it come from? The kinetic energy of the interacting molecules? Macroscopically it’s easy to see how a collision between two molecules could change the vibrational and/or rotation energy levels of a molecule. What does a collision between between molecules look like in terms of the wave functions of both. I’ve never seen this. It has to have been worked out for single particle physics in an accelerators, but that’s something I’ve never studied.

One molecule inducing a transient dipole in another, which then induces a complementary dipole in the first molecule, seems like a lot of handwaving to me. It also appears to be getting something for nothing contradicting the second law of thermodynamics.

Any thoughts from the physics mavens out there?

I sincerely hope it works, but I’m very doubtful

A fascinating series of papers offers hope (in the form of a small molecule) for the truly horrible Werdnig Hoffman disease which basically kills infants by destroying neurons in their spinal cord. For why this is especially poignant for me, see the end of the post.

First some background:

Our genes occur in pieces. Dystrophin is the protein mutated in the commonest form of muscular dystrophy. The gene for it is 2,220,233 nucleotides long but the dystrophin contains ‘only’ 3685 amino acids, not the 770,000+ amino acids the gene could specify. What happens? The whole gene is transcribed into an RNA of this enormous length, then 78 distinct segments of RNA (called introns) are removed by a gigantic multimegadalton machine called the spliceosome, and the 79 segments actually coding for amino acids (these are the exons) are linked together and the RNA sent on its way.

All this was unknown in the 70s and early 80s when I was running a muscular dystrophy clininc and taking care of these kids. Looking back, it’s miraculous that more of us don’t have muscular dystrophy; there is so much that can go wrong with a gene this size, let along transcribing and correctly splicing it to produce a functional protein.

One final complication — alternate splicing. The spliceosome removes introns and splices the exons together. But sometimes exons are skipped or one of several exons is used at a particular point in a protein. So one gene can make more than one protein. The record holder is something called the Dscam gene in the fruitfly which can make over 38,000 different proteins by alternate splicing.

There is nothing worse than watching an infant waste away and die. That’s what Werdnig Hoffmann disease is like, and I saw one or two cases during my years at the clinic. It is also called infantile spinal muscular atrophy. We all have two genes for the same crucial protein (called unimaginatively SMN). Kids who have the disease have mutations in one of the two genes (called SMN1) Why isn’t the other gene protective? It codes for the same sequence of amino acids (but using different synonymous codons). What goes wrong?

[ Proc. Natl. Acad. Sci. vol. 97 pp. 9618 - 9623 '00 ] Why is SMN2 (the centromeric copy (e.g. the copy closest to the middle of the chromosome) which is normal in most patients) not protective? It has a single translationally silent nucleotide difference from SMN1 in exon 7 (e.g. the difference doesn’t change amino acid coded for). This disrupts an exonic splicing enhancer and causes exon 7 skipping leading to abundant production of a shorter isoform (SMN2delta7). Thus even though both genes code for the same protein, only SMN1 actually makes the full protein.

Intellectually fascinating but ghastly to watch.

This brings us to the current papers [ Science vol. 345 pp. 624 - 625, 688 - 693 '14 ].

More background. The molecular machine which removes the introns is called the spliceosome. It’s huge, containing 5 RNAs (called small nuclear RNAs, aka snRNAs), along with 50 or so proteins with a total molecular mass again of around 2,500,000 kiloDaltons. Think about it chemists. Design 50 proteins and 5 RNAs with probably 200,000+ atoms so they all come together forming a machine to operate on other monster molecules — such as the mRNA for Dystrophin alluded to earlier. Hard for me to believe this arose by chance, but current opinion has it that way.

Splicing out introns is a tricky process which is still being worked on. Mistakes are easy to make, and different tissues will splice the same pre-mRNA in different ways. All this happens in the nucleus before the mRNA is shipped outside where the ribosome can get at it.

The papers describe a small molecule which acts on the spliceosome to increase the inclusion of SMN2 exon 7. It does appear to work in patient cells and mouse models of the disease, even reversing weakness.

Why am I skeptical? Because just about every protein we make is spliced (except histones), and any molecule altering the splicing machinery seems almost certain to produce effects on many genes, not just SMN2. If it really works, these guys should get a Nobel.

Why does the paper grip me so. I watched the beautiful infant daughter of a cop and a nurse die of it 30 – 40 years ago. Even with all the degrees, all the training I was no better for the baby than my immigrant grandmother dispensing emotional chicken soup from her dry goods store (she only had a 4th grade education). Fortunately, the couple took the 25% risk of another child with WH and produced a healthy infant a few years later.

A second reason — a beautiful baby grandaughter came into our world 24 hours ago.

Poets and religious types may intuit how miraculous our existence is, but the study of molecular biology proves it (to me at least).

As if the job shortage for organic/medicinal chemists wasn’t bad enough

Will synthetic organic chemists be replaced by a machine? Today’s (7 August ’14) Nature (vol. 512 pp. 20 – 22) describes RoboChemist. As usual the job destruction is the fruit of the species being destroyed. Nothing new here — “The Capitalists will sell us the rope with which we will hang them.” — Lenin. “I would consider it entirely feasible to build a synthesis machine which could make any one of a billion defined small molecules on demand” says one organic chemist.

The design of the machine is already being studied, but with a rather paltry grant (1.2 million dollars). Even worse, for the thinking chemist, the choice of reactants and reactions to build the desired molecule will be made by the machine (given a knowledge base, and the algorithms that experienced chemists use, assuming they can be captured by a set of rules). E. J. Corey tried to do this automatically years ago with a program called LHASA (Logic and Heuristics Applied to Synthetic Analysis), but it never took off. Corey formalized what chemists had been doing all along — see http://luysii.wordpress.com/2010/06/20/retrosynthetic-analysis-and-moliere/

Another attempt along these lines is Chematica, which recently has had some success. A problem with using the chemical literature, is that only the conditions for a successful reaction are published. A synthetic program needs to know what doesn’t work as much as it needs to know what does. This is an important problem in the medical/drug literature where only studies showing a positive effect are published. There’s a great chapter in “How Not to Be Wrong” concerning the “International Journal of Haruspicy” which publishes only statically significant results for predicting the future reading sheep entrails. They publish a lot of stuff because some 400 Haruspicists in different labs are busy performing multiple experiments, 5% of which reach statistical significance. Previously drug companies had to publish only successful clinical trials. Now they’ll be going into a database regardless of outcome.

Automated machinery for making polynucleotides and poly peptides already exists, but here the reactions are limited. Still, the problem of getting the same reaction to work over and over with different molecules of the same class (amino acids, nucleotides) has been solved.

The last sentence is the most chilling “And with a large workforce of graduate students to draw on, academic labs often have little incentive to automate.” Academics — the last Feudal system left standing.

However, telephone operators faced the same fate years ago, due to automatic switching machinery. Given the explosion of telephone volume 50 years ago, there came a point where every woman in the USA would have worked for the phone company to handle the volume.

A similar moment of terror occurred in my field (clinical neurology) years ago with the invention of computerized axial tomography (CAT scans). All our diagnostic and examination skills (based on detecting slight deviations from normal function) would be out the window, when the CAT scan showed what was structurally wrong with the brain. Diagnosis was possible because abnormalities in structure invariably occurred earlier than abnormalities in function. Didn’t happen. We’d get calls – we found this thing on the CAT scan. What does it mean?

Even this wonderful machine which can make any molecule you wish, will not tell you what cellular entity to attack, what the target does, and how attacking it will produce a therapeutically useful result.

Getting cytoplasm out of a single cell without killing it

It’s easy to see what cells are doing metabolically. Just take a million or so, grind them up and measure what you want. If this sounds crude to you, you’re right. We’ve learned a lot this way, but wouldn’t it be nice to take a single cell and get a sample of its cytoplasm (or it’s nucleus) without killing it. A technique described in the 29 July PNAS (vol. pp. 10966 – 10971 ’14) does just that. It’s hardly physiologic, as cells are grown on a layer of polycarbonate containing magnetically active carbon nanoTubes http://en.wikipedia.org/wiki/Carbon_nanotube covered in L-tyrosine polymers. The nanotubes are large enough to capture anything smaller than an organelle (1,000 Angstrom, 100 nanoMeter diameter, 15,000 Angstroms long). Turn on a magnetic underneath the polycarbonate, and they puncture the overlying cell and are filled with cytoplasm. Reverse the magnetic field and they come out, carrying the metabolites with them. Amazingly, there was no significant impact on cell viability or proliferation. Hardly physiologic but far better than what we’ve had.

It’s a long way from drug development, but wouldn’t it be nice to place your drug candidate inside a cell and watch what it’s doing?

A Troublesome Inheritance – IV — Chapter 3

Chapter III of “A Troublesome Inheritance” contains a lot of very solid molecular genetics, and a lot of unfounded speculation. I can see why the book has driven some otherwise rational people bonkers. Just because Wade knows what he’s talking about in one field, doesn’t imply he’s competent in another.

Several examples: p. 41 “”Nonethless, it is reasonable to assume that if traits like skin color have evolved in a population, the same may be true of its social behavior.” Consider yes, assume no.

p. 42 “The society of living chimps can thus with reasonable accuracy stand as a surrogate for the joint ancester” (of humans and chimps — thought to be about 7 megaYears ago) and hence describe the baseline from which human social behavior evolved.” I doubt this.

The chapter contains many just so stories about the evolution of chimp and human societies (post hoc propter hoc). Plausible, but not testable.

Then follows some very solid stuff about the effects of the hormone oxytocin (which causes lactation in nursing women) on human social interaction. Then some speculation on the ways natural selection could work on the oxytocin system to make people more or less trusting. He lists several potential mechanisms for this (1) changes in the amount of oxytocin made (2) increasing the number of protein receptors for oxytocin (3) making each receptor bind oxytocin more tightly. This shows that Wade has solid molecular biological (and biological) chops.

He quotes a Dutch psychologist on his results with oxytocin and sociality — unfortunately, there have been too many scandals involving Dutch psychologists and sociologists to believe what he says until its replicated (Google Diederik Stapel, Don Poldermans, Jens Forster, Markus Denzler if you don’t believe me). It’s sad that this probably honest individual is tarred with that brush but he is.

p. 59 — He notes that the idea that human behavior is solely the result of social conditions with no genetic influence is appealing to Marxists, who hoped to make humanity behave better by designing better social conditions. Certainly, much of the vitriol heaped on the book has come from the left. A communist uncle would always say ‘it’s the system’ to which my father would reply ‘people will corrupt any system’.

p. 61 — the effect of mutations of lactose tolerance on survival on society are noted — people herding cattle and drinking milk, survive better if their gene to digest lactose (the main sugar in milk) isn’t turned off after childhood. If your society doesn’t herd animals, there is no reason for anyone to digest milk after weaning from the breast. The mutations aren’t in the enzyme digesting lactose, but in the DNA that turns on expression of the gene for the enzyme (e.g. the promoter). Interestingly, 3 separate mutations in African herders have been found to do this, and different from the one that arose in the Funnel Beaker Culture of Scandinavia 6,000 yers ago. This is a classic example of natural selection producing the same phenotypic effect by separate mutations.

There is a much bigger biological fish to be fried here, which Wade doesn’t discuss. It takes energy to make any protein, and there is no reason to make a protein to help you digest milk if you aren’t nursing, and one very good reason not to — it wastes metabolic energy, something in short supply in humans as they lived until about 15,000 years ago. So humans evolved a way not to make the protein in adult life. The genetic change is in the DNA controlling protein production not the protein itself.

You may have heard it said that we are 98% Chimpanzee. This is true in the sense that our 20,000 or so proteins are that similar to the chimp. That’s far from the whole story. This is like saying Monticello and Independence Hall are just the same because they’re both made out of bricks. One could chemically identify Monticello bricks as coming from the Virginia piedmont, and Independence Hall bricks coming from the red clay of New Jersey, but the real difference between the buildings is the plan.

It’s not the proteins, but where and when and how much of them are made. The control for this (plan if you will) lies outside the genes for the proteins themselves, in the rest of the genome. The control elements have as much right to be called genes, as the parts of the genome coding for amino acids. Granted, it’s easier to study genes coding for proteins, because we’ve identified them and know so much about them. It’s like the drunk looking for his keys under the lamppost because that’s where the light is.

p. 62 — There follows some description of the changes of human society from hunter gathering, to agrarian, to the rise of city states, is chronicled. Whether adaptation to different social organizations produced genetic changes permitting social adaptation or were the cause of it isn’t clear. Wade says “changes in social behavior, has most probably been molded by evolution, through the underlying genetic changes have yet to be identified.” This assumes a lot, e.g. that genetic changes are involved. I’m far from sure, but the idea is not far fetched. Stating that genetic changes have never, and will never shape society, is without any scientific basis, and just as fanciful as many of Wade’s statements in this chapter. It’s an open question, which is really all Wade is saying.

In defense of Wade’s idea, think about animal breeding as Darwin did extensively. The Origin of Species (worth a read if you haven’t already read it) is full of interchanges with all sorts of breeders (pigeons, cattle). The best example we have presently are the breeds of dogs. They have very different personalities — and have been bred for them, sheep dogs mastifs etc. etc. Have a look at [ Science vol. 306 p. 2172 '04, Proc. Natl. Acad. Sci. vol. 101 pp. 18058 - 18063 '04 ] where the DNA of variety of dog breeds was studied to determine which changes determined the way they look. The length of a breed’s snout correlated directly with the number of repeats in a particular protein (Runx-2). The paper is a decade old and I’m sure that they’re starting to look at behavior.

More to the point about selection for behavioral characteristics, consider the domestication of the modern dog from the wolf. Contrast the dog with the chimp (which hasn’t been bred).

[ Science vol. 298 pp. 1634 - 1636 '02 ] Chimps are terrible at picking up human cues as to where food is hidden. Cues would be something as obvious as looking at the containing, pointing at the container or even touching it. Even those who eventually perform well, take dozens of trials or more to learn it. When tested in more difficult tests requiring them to show flexible use of social cues they don’t

This paper shows that puppies (raised with no contact with humans) do much better at reading humans than chimps. However wolf cubs do not do better than the chimps. Even more impressively, wolf cubs raised by humans don’t show the same skills. This implies that during the process of domestication, dogs have been selected for a set of social cognitive abilities that allow them to communicate with humans in unique ways. Dogs and wolves do not perform differently in a non-social memory task, ruling out the possibility that dogs outperform wolves in all human guided tasks.

All in all, a fascinating book with lots to think about, argue with, propose counterarguments, propose other arguments in support (as I’ve just done), etc. etc. Definitely a book for those who like to think, whether you agree with it all or not.

Old dog does new(ly discovered) tricks

One of the evolutionarily oldest enzyme classes is aaRS (for amino acyl tRNA synthetase). Every cell has them including bacteria. Life as we know it wouldn’t exist without them. Briefly they load tRNA with the appropriate amino acid. If this Greek to you, look at the first 3 articles in https://luysii.wordpress.com/category/molecular-biology-survival-guide/.

Amino acyl tRNA syntheses are enzymes of exquisite specificity, having to correctly match up 20 amino acids to some 61 different types of tRNAs. Mistakes in the selection of the correct amino acid occurs every 1/10,000 to 1/100,000, and in the selection of the correct tRNA every 1/1,000,000. The lower tRNA error rate is due to the fact that tRNAs are much larger than amino acids, and so more contacts between enzyme and tRNA are possible.

As the tree of life was ascended from bacteria over billions of years, 13 new protein domains which have no obvious association with aminoacylation have been added to AARS genes. More importantly, the additions have been maintained over the course of evolution (with no change in the primary function of the synthetase). Some of the new domains are appended to each of several synthetases, while others are specific to a single synthetase. The fact that they’ve been retained implies they are doing something that natural selection wants (teleology inevitably raises its ugly head with any serious discussion of molecular biology or cellular physiology — it’s impossible to avoid).

[ Science vol.345 pp 328 - 332 '14 ] looked at what mRNAs some 37 different AARS genes were transcribed into. Six different human tissues were studied this way. Amazingly, 79% of the 66 in-frame splice variants removed or disrupted the aaRS catalytic domain. . The AARS for histidine had 8 inframe splice variants all of which removed the catalytic domain. 60/70 variants losing the catalytic domain (they call these catalytic nulls) retained at least one of the 13 added domains in higher eukaryotes. Some of the transcripts were tissue specific (e.g. present in some of the 6 tissues but not all).

Recent work has shown roles for specific AARSs in a variety of pathways — blood vessel formation, inflammation, immune response, apoptosis, tumor formation, p53 signaling. The process of producing a completely different function for a molecule is called exaptation — to contrast it with adaptation.

Up to now, when a given protein was found to have enzymatic activity, the book on what that protein did was closed (with the exception of the small GTPases). End of story. Yet here we have cells spending the metabolic energy to make an enzymatically dead protein (aaRSs are big — the one for alanine has nearly 1,000 amino acids). Teleology screams — what is it used for? It must be used for something! This is exactly where chemistry is silent. It can explain the incredible selectivity and sensitivity of the enzyme but not what it is ‘for’. We have crossed the Cartesian dualism between flesh and spirit.

Could this sort of thing be the tip of the iceberg? We know that splice variants of many proteins are common. Could other enzymes whose function was essentially settled once substrates were found, be doing the same thing? We may have only 20,000 or so protein coding genes, but 40,000, 60,000, . . . or more protein products of them, each with a different biological function.

So aaRSs are very old molecular biological dogs, who’ve been doing new tricks all along. We just weren’t smart enough to see them (’till now).

Novels may have only 7 basic plots, but molecular biology continues to surprise and enthrall.

Follow

Get every new post delivered to your Inbox.

Join 67 other followers