Category Archives: Molecular Biology

A very UNtheoretical approach to cancer diagnosis

We have tons of different antibodies in our blood. Without even taking mutation into account we have 65 heavy chain genes, 27 diversity segments, and 6 joining regions for them (making 10,530) possibilities — then there are 40 genes for the kappa light chains and 30 for the lambda light chains or over 1,200 * 10,530. That’s without the mutations we know that do occur to increase antibody affinity. So the number of antibodies probably ramming around in our blood is over a billion (I doubt that anyone has counted then, just has no one has ever counted the neurons in our brain). Antibodies can bind to anything — sugars, fats, but we think of them as mostly binding to protein fragments.

We also know that cancer is characterized by mutations, particularly in the genes coding for proteins. Many of the these mutations have never been seen by the immune system, so they act as neoantigens. So what [ Proc. Natl. Acad. Sci. vo. 111 pp. E3072 - E3080 '14 ] did was make a chip containing 10,000 peptides, and saw which of them were bound by antibodies in the blood.

The peptides were 20 amino acids long, with 17 randomly chosen amino acids, and a common 3 amino acid linker to the chip. While 10,000 seems like a lot of peptides, it is a tiny fraction (actually 10^-18
of the 2^17 * 10^17 = 1.3 * 10^22 possible 17 amino acid peptides).

The blood was first diluted 500x so blood proteins other than antibodies don’t bind significantly to the arrays. The assay is disease agnostic. The pattern of binding of a given person’s blood to the chip is called an immunosignature.

What did they measure? 20 samples from each of five cancer cohorts collected from multiple geographic sites and 20 noncancer samples. A reference immunosignature was generated. Then 120 blinded samples from the same diseases gave 95$% classification accuracy. To investigate the breadth of the approach and test sensitivity, the immunosignatures 75% of over 1,500 historical samples (some over 10 years old) comprising 14 different diseases were used as training, then the other 25% were read blind with an accuracy of over 98% — not too impressive, they need to get another 1,500 samples. Once you’ve trained on 75% of the sample space, you’d pretty much expect the other 25% to look the same.

The immunosignature of a given individual consists of an overlay of the patterns from the binding signals of many of the most prominent circulating antibodies. Some are present in everyone, some are unique.

A 2002 reference (Molecular Biology of the Cell 4th Edition) states that there are 10^9 antibodies circulating in the blood. How can you pick up a signature on 10K peptides from this. Presumably neoAntigens from cancer cells elicit higher afifnity antibodies then self-antigens. High affiity monoclonals can be diluted hundreds of times without diminishing the signal.

The next version of the immunosignature peptide microArray under development contains over 300,000 peptides.

The implication is that each cancer and each disease produces either different antigens and or different B cell responses to common antigens.

Since the peptides are random, you can’t align the peptides in the signature to the natural proteomic space to find out what the antibody is reacing to.

It’s a completely atheoretical approach to diagnosis, but intriguing. I’m amazed that such a small sample of protein space can produce a significant binding pattern diagnostic of anything.

It’s worth considering just what a random peptide of 17 amino acids actually is. How would you make one up? Would you choose randomly giving all 20 amino acids equal weight, or would you weight the probability of a choice by the percentage of that amino acid in the proteome of the tissue you are interested in. Do we have such numbers? My guess is that proline, glycine and alanine would the most common amino acids — there is so much collagen around, and these 3 make up a high percentage of the amino acids in the various collagens we have (over 15 at least).

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).

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.

Here’s a drug target for schizophrenia and other psychiatric diseases

All agree that any drug getting schizophrenics back to normal would be a blockbuster. The more we study its genetics and biochemistry the harder the task becomes. Here’s one target — neuregulin1, one variant of which is strongly associated with schizophrenia (in Iceland).

Now that we know that neuregulin1 is a potential target, why should discovering a drug to treat schizophrenia be so hard? The gene stretches over 1.2 megaBases and the protein contains some 640 amino acids. Cells make some 30 different isoforms by alternative splicing of the gene. Since the gene is so large one would expect to find a lot of single nucleotide polymorphisms (SNPs) in the gene. Here’s some SNP background.

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 any 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.

Well it’s 10 years later, and a mere 23,094 SNPs have been found in the neuregulin gene, of which 40 have been associated with schizophrenia. Unfortunately most of them aren’t in regions of the gene which code for amino acids (which is to be expected as 640 * 3 = 1920 nucleotides are all you need for coding out of the 1,200,000 nucleotides making up the gene). These SNPs probably alter the amount of the protein expressed but as of now very little is known (even whether they increase or decrease neuregulin1 protein levels).

An excellent review of Neuregulin1 and schizophrenia is available [ Neuron vol. 83 pp. 27 - 49 '14 ] You’ll need a fairly substantial background in neuroanatomy, neuroembryology, molecular biology, neurophysiology to understand all of it. Included are some fascinating (but probably incomprehensible to the medicinal chemist) material on the different neurophyiologic abnormalities associated with different SNPs in the gene.

Here are a few of the high points (or depressing points for drug discovery) of the review. Neuregulin1 is a member of a 6 gene family, all fairly similar and most expressed in the brain. All of them have multiple splicing isoforms, so drug selectivity between them will be tricky. Also SNPs associated with increased risk of schizophrenia have been found in family members numbers 2, 3 and 6 as well, so neuregulin1 not be the actual target you want to hit.

It gets worse. The neuregulins bind to a family of receptors (the ERBBs) having 4 members. Tending to confirm the utility of the neuregulins as a drug target is the fact that SNPs in the ERBBs are also associated with schizophrenia. So which isoform of which neuregulin binding to which iso form of which ERBB is the real target? Knowledge isn’t always power.

A large part of the paper is concerned with the function of the neuregulins in embryonic development of the brain, leading the the rather depressing thought that the schizophrenic never had a change, having an abnormal brain to begin with. A drug to reverse such problems seems only a hope.

The neuregulin/EBBB system is only one of many genes which have been linked to schizophrenia. So it looks like a post of a 4 years ago on Schizophrenia is largely correct — http://luysii.wordpress.com/2010/04/25/tolstoy-was-right-about-hereditary-diseases-imagine-that/

Happy hunting. It’s a horrible disease and well worth the effort. We’re just beginning to find out how complex it really is. Hopefully we’ll luck out, as we did with the phenothiazines, the first useful antipsychotics.

“A Troublesome Inheritance” – I

One of the joys of a deep understanding of chemistry, is the appreciation of the ways in which life is constructed from the most transient of materials. Presumably the characteristics of living things that we can see (the phenotype) will someday be traceable back to the proteins, nucleic acids,and small metabolites (lipids, sugars, etc..) making us up.

For the time being we must content ourselves with understanding the code (our genes) and how it instructs the development of a trillion celled organism from a fertilized egg. This brings us to Wade’s book, which has been attacked as racist, by anthropologists, sociologists and other lower forms of animal life.

Their position is that races are a social, not a biological construct and that differences between societies are due to the way they are structured, not by differences in the relative frequency of the gene variants (alleles) in the populations making them up. Essentially they are saying that evolution and its mechanism descent with modification under natural selection, does not apply to humanity in the last 50,000 years when the first modern humans left Africa.

Wade disagrees. His book is very rich in biologic detail and one post about it discussing it all would try anyone’s attention span. So I’m going to go through it, page by page, commenting on the material within (the way I’ve done for some chemistry textbooks), breaking it up in digestible chunks.

As might be expected, there will be a lot of molecular biology involved. For some background see the posts in https://luysii.wordpress.com/category/molecular-biology-survival-guide/. Start with http://luysii.wordpress.com/2010/07/07/molecular-biology-survival-guide-for-chemists-i-dna-and-protein-coding-gene-structure/ and follow the links forward.

Wade won me over very quickly (on page 3), by his accurate and current citations to the current literature. He talks about how selection on a mitochondrial protein helped Tibetans to live at high altitude (while the same mutation those living at low altitudes leads to blindness). Some 25% Tibetans have the mutation while it is rare among those living at low altitudes.
Here’s my post of 10 June 2012 ago on the matter. That’s all for now

Have Tibetans illuminated a path to the dark matter (of the genome)?

I speak not of the Dalai Lama’s path to enlightenment (despite the title). Tall people tend to have tall kids. Eye color and hair color is also hereditary to some extent. Pitched battles have been fought over just how much of intelligence (assuming one can measure it) is heritable. Now that genome sequencing is approaching a price of $1,000/genome, people have started to look at variants in the genome to help them find the genetic contribution to various diseases, in the hopes of understanding andtreating them better.

Frankly, it’s been pretty much of a bust. Height is something which is 80% heritable, yet the 20 leading candidate variants picked up by genome wide association studies (GWAS) account for 3% of the variance [ Nature vol. 461 pp. 458 - 459 '09 ]. This has happened again and again particularly with diseases. A candidate gene (or region of the genome), say for schizophrenia, or autism, is described in one study, only to be shot down by the next. This is likely due to the fact that many different genetic defects can be associated with schizophrenia — there are a lot of ways the brain cannot work well. For details — see http://luysii.wordpress.com/2010/04/25/tolstoy-was-right-about-hereditary-diseases-imagine-that/. or see http://luysii.wordpress.com/2010/07/29/tolstoy-rides-again-autism-spectrum-disorder/.

Typically, even when an association of a disease with a genetic variant is found, the variant only increases the risk of the disorder by 2% or less. The bad thing is that when you lump them all of the variants you’ve discovered together (for something like height) and add up the risk, you never account for over 50% of the heredity. It isn’t for want of looking as by 2010 some 600 human GWAS studies had been published [ Neuron vol. 68 p. 182 '10 ]. Yet lots of the studies have shown various disease to have a degree of heritability (particularly schizophrenia). The fact that we’ve been unable to find the DNA variants causing the heritability was totally unexpected. Like the dark matter in galaxies, which we know is there by the way the stars spin around the galactic center, this missing heritability has been called the dark matter of the genome.

Which brings us to Proc. Natl. Acad. Sci. vol. 109 pp. 7391 – 7396 ’12. It concerns an awful disease causing blindness in kids called Leber’s hereditary optic neuropathy. The ’cause’ has been found. It is a change of 1 base from thymine to cytosine in the gene for a protein (NADH dehydrogenase subunit 1) causing a change at amino acid #30 from tyrosine to histidine. The mutation is found in mitochondrial DNA not nuclear DNA, making it easier to find (it occurs at position 3394 of the 16,569 nucleotide mitochondrial DNA).

Mitochondria in animal cells, and chloroplasts in plant cells, are remnants of bacteria which moved inside cells as we know them today (rest in peace Lynn Margulis).

Some 25% of Tibetans have the 3394 T–>C mutations, but they see just fine. It appears to be an adaptation to altitude, because the same mutation is found in nonTibetans on the Indian subcontinent living about 1500 meters (about as high as Denver). However, if you have the same genetic change living below this altitude you get Lebers.

This is a spectacular demonstration of the influence of environment on heredity. Granted that the altitude you live at is a fairly impressive environmental change, but it’s at least possible that more subtle changes (temperature, humidity, air conditions etc. etc.) might also influence disease susceptibility to the same genetic variant. This certainly is one possible explanation for the failure of GWAS to turn up much. The authors make no mention of this in their paper, so these ideas may actually be (drumroll please) original.

If such environmental influences on the phenotypic expression of genetic changes are common, it might be yet another explanation for why drug discovery is so hard. Consider CETP (Cholesterol Ester Transfer Protein) and the very expensive failure of drugs inhibiting it. Torcetrapib was associated with increased deaths in a trial of 15,000 people for 18 – 20 months. Perhaps those dying somehow lived in a different environment. Perhaps others were actually helped by the drug

Why marihuana scares me

There’s an editorial in the current Science concerning how very little we know about the effects of marihuana on the developing adolescent brain [ Science vol. 344 p. 557 '14 ]. We know all sorts of wonderful neuropharmacology and neurophysiology about delta-9 tetrahydrocannabinol (d9-THC) — http://en.wikipedia.org/wiki/Tetrahydrocannabinol The point of the authors (the current head of the Amnerican Psychiatric Association, and the first director of the National (US) Institute of Drug Abuse), is that there are no significant studies of what happens to adolescent humans (as opposed to rodents) taking the stuff.

Marihuana would the first mind-alteraing substance NOT to have serious side effects in a subpopulation of people using the drug — or just about any drug in medical use for that matter.

Any organic chemist looking at the structure of d9-THC (see the link) has to be impressed with what a lipid it is — 21 carbons, only 1 hydroxyl group, and an ether moiety. Everything else is hydrogen. Like most neuroactive drugs produced by plants, it is quite potent. A joint has only 9 milliGrams, and smoking undoubtedly destroys some of it. Consider alcohol, another lipid soluble drug. A 12 ounce beer with 3.2% alcohol content has 12 * 28.3 *.032 10.8 grams of alcohol — molecular mass 62 grams — so the dose is 11/62 moles. To get drunk you need more than one beer. Compare that to a dose of .009/300 moles of d9-THC.

As we’ve found out — d9-THC is so potent because it binds to receptors for it. Unlike ethanol which can be a product of intermediary metabolism, there aren’t enzymes specifically devoted to breaking down d9-THC. In contrast, fatty acid amide hydrolase (FAAH) is devoted to breaking down anandamide, one of the endogenous compounds d9-THC is mimicking.

What really concerns me about this class of drugs, is how long they must hang around. Teaching neuropharmacology in the 70s and 80s was great fun. Every year a new receptor for neurotransmitters seemed to be found. In some cases mind benders bound to them (e.g. LSD and a serotonin receptor). In other cases the endogenous transmitters being mimicked by a plant substance were found (the endogenous opiates and their receptors). Years passed, but the receptor for d9-thc wasn’t found. The reason it wasn’t is exactly why I’m scared of the drug.

How were the various receptors for mind benders found? You throw a radioactively labelled drug (say morphine) at a brain homogenate, and purify what it is binding to. That’s how the opiate receptors etc. etc. were found. Why did it take so long to find the cannabinoid receptors? Because they bind strongly to all the fats in the brain being so incredibly lipid soluble. So the vast majority of stuff bound wasn’t protein at all, but fat. The brain has the highest percentage of fat of any organ in the body — 60%, unless you considered dispersed fatty tissue an organ (which it actually is from an endocrine point of view).

This has to mean that the stuff hangs around for a long time, without any specific enzymes to clear it.

It’s obvious to all that cognitive capacity changes from childhood to adult life. All sorts of studies with large numbers of people have done serial MRIs children and adolescents as the develop and age. Here are a few references to get you started [ Neuron vol. 72 pp. 873 - 884, 11, Proc. Natl. Acad. Sci. vol. 107 pp. 16988 - 16993 '10, vol. 111 pp. 6774 -= 6779 '14 ]. If you don’t know the answer, think about the change thickness of the cerebral cortex from age 9 to 20. Surprisingly, it get thinner, not thicker. The effect happens later in the association areas thought to be important in higher cognitive function, than the primary motor or sensory areas. Paradoxical isn’t it? Based on animal work this is thought to be due pruning of synapses.

So throw a long-lasting retrograde neurotransmitter mimic like d9-THC at the dynamically changing adolescent brain and hope for the best. That’s what the cited editorialists are concerned about. We simply don’t know and we should.

Having been in Cambridge when Leary was just getting started in the early 60’s, I must say that the idea of tune in turn on and drop out never appealed to me. Most of the heavy marihuana users I’ve known (and treated for other things) were happy, but rather vague and frankly rather dull.

Unfortunately as a neurologist, I had to evaluate physician colleagues who got in trouble with drugs (mostly with alcohol). One very intelligent polydrug user MD, put it to me this way — “The problem is that you like reality, and I don’t”.

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