Category Archives: Medicine in general

Is natural selection disprovable?

One of the linchpins of evolutionary theory is that natural selection works by increased reproductive success of the ‘fittest’. Granted that this is Panglossian in its tautology — of course the fittest is what survives, so of course it has greater reproductive success.

So decreased reproductive success couldn’t be the result of natural selection could it? A recent paper http://www.sciencemag.org/content/348/6231/180.full.pdf says that is exactly what has happened, and in humans to boot, not in some obscure slime mold or the like.

The work comes from in vitro fertilization which the paper says is responsible for 2 -3 % of all children born in developed countries — seems high. Maternal genomes can be sequenced and the likelihood of successful conception correlated with a variety of variants. It was found that there is a strong association between change in just one nucleotide (e.g. a single nucleotide polymorphism or SNP) and reproductive success. The deleterious polymorphism (rs2305957) decreases reproductive success. This is based on 15,388 embryos from 2,998 mothers sampled at the day-5 blastocyst stage.

What is remarkable is that the polymorphism isn’t present in Neanderthals (from which modern humans diverged between 100,000 and 400,000 year ago). It is in an area of the genome which has the characteristics of a ‘selective sweep’. Here’s the skinny

A selective sweep is the reduction or elimination of variation among the nucleotides in neighbouring DNA of a mutation as the result of recent and strong positive natural selection.

A selective sweep can occur when a new mutation occurs that increases the fitness of the carrier relative to other members of the population. Natural selection will favour individuals that have a higher fitness and with time the newly mutated variant (allele) will increase in frequency relative to other alleles. As its prevalence increases, neutral and nearly neutral genetic variation linked to the new mutation will also become more prevalent. This phenomenon is called genetic hitchhiking. A strong selective sweep results in a region of the genome where the positively selected haplotype (the mutated allele and its neighbours) is essentially the only one that exists in the population, resulting in a large reduction of the total genetic variation in that chromosome region.

So here we have something that needs some serious explaining — something decreasing fecundity which is somehow ‘fitter’ (by the definition of fitness) because it spread in the human population. The authors gamely do their Panglossian best explaining “the mitotic-error phenotype (which causes decreased fecundity) may be maintained by conferring both a deleterious effect on maternal fecundity and a possible beneficial effect of obscured paternity via a reduction in the probability of successful pregnancy per intercourse. This hypothesis is based on the fact that humans possess a suite of traits (such as concealed ovulation and constant receptivity) that obscure paternity and may have evolved to increase paternal investment in offspring.

Nice try fellas, but this sort of thing is a body blow to the idea of natural selection as increased reproductive success.

There is a way out however, it is possible that what is being selected for is something controlled near to rs2305957 so useful, that it spread in our genome DESPITE decreased fecundity.

Don’t get me wrong, I’m not a creationist. The previous post https://luysii.wordpress.com/2015/04/07/one-reason-our-brain-is-3-times-that-of-a-chimpanzee/ described some of the best evidence we have in man for another pillar of evolutionary theory — descent with modification. Here duplication of a single gene since humans diverged from chimps causes a massive expansion of the gray matter of the brain (cerebral cortex).

Fascinating

Addendum 13 April

I thought the following comment was so interesting that it belongs in the main body of the text

Handles:

Mutations dont need to confer fitness in order to spread through the population. These days natural selection is considered a fairly minor part of evolution. Most changes become fixed as the result of random drift, and fitness is usually irrelevant. “Nearly neutral theory” explains how deleterious mutations can spread through a population, even without piggybacking on a beneficial mutation; no need for panglossian adaptive hypotheses.

Here’s my reply

Well, the authors of the paper didn’t take this line, but came up with a rather contorted argument to show why decreased fecundity might be a selective advantage, rather than just saying it was random drift. They also note genomic evidence for a ‘selective sweep’ — decreased genomic heterogeneity around the SNP.

No wonder we get sick

“It is estimated that a human cell repairs 10,000 – 20,000 DNA lesions per day” This is the opening sentence of Proc. Natl. Acad. Sci. vol. 112 pp. 3997 – 4002 ’15, but no source for this estimate is given. The lesions range from single and double strand breaks in the sugar phosphate backbone of the DNA helix, to hydrolytic losses of a DNA base from the backbone, to chemical modification of the DNA bases themselves — oxidation etc. etc.

What needs explaining then, is why we stay as well as we do. https://luysii.wordpress.com/2009/09/17/the-solace-of-molecular-biology/

Should pregnant women smoke pot?

Well, maybe this is why college board scores have declined so much in recent decades that they’ve been normed upwards. Given sequential MRI studies on brain changes throughout adolescence (with more to come), we know that it is a time of synapse elimination. (this will be the subject of another post). We also know that endocannabinoids, the stuff in the brain that marihuana is mimicking, are retrograde messengers there, setting synaptic tone for information transmission between neurons.

But there’s something far scarier in a paper that just came out [ Proc. Natl. Acad. Sci. vol. 112 pp. 3415 – 3420 ’15 ]. Hedgehog is a protein so named because its absence in fruitflies (Drosophila) causes excessive bristles to form, making them look like hedgehogs. This gives you a clue that Hedgehog signaling is crucial in embryonic development. A huge amount is known about it with more being discovered all the time — for far more details than I can provide see http://en.wikipedia.org/wiki/Hedgehog_signaling_pathway.

Unsurprisingly, embryonic development of the brain involves hedgehog, e,g, [ Neuron vol. 39 pp. 937 – 950 ’03 ] Hedgehog (Shh) signaling is essential for the establishment of the ventral pattern along the whole neuraxis (including the telencephalon). It plays a mitogenic role in the expansion of granule cell precursors during CNS development. This work shows that absence of Shh decreases the number of neural progenitors in the postnatal subventricular zone and hippocampus. Similarly conditional inactivation of smoothened results in the formation of fewer neurospheres from progenitors in the subventricular zone. Stimulation of the hedgehog pathway in the mature brain results in elevated proliferation in telencephalic progenitors. It’s a lot of unfamiliar jargon, but you get the idea.

Of interest is the fact that the protein is extensively covalently modified by lipids (cholesterol at the carboxy terminal end and palmitic acid at the amino terminal end. These allow hedgehog to bind to its receptor (smoothened). It stands to reason that other lipids might block this interaction. The PNAS work shows this is exactly the case (in Drosophila at least). One or more lipids present in Drosophila lipoprotein particles are needed in vivo to keep Hedgehog signaling turned off in wing discs (when hedgehog ligand isn’t around). The lipids destabilize Smoothtened. This work identifies endocannabinoids as the inhibitory lipids from extracts of human very low density lipoprotein (VLDL).

It certainly is a valid reason for women not to smoke pot while pregnant. The other problem with the endocannabinoids and exocannabinoids (e.g. delta 9 tetrahydrocannabinol), is that they are so lipid soluble they stick around for a long time — see https://luysii.wordpress.com/2014/05/13/why-marihuana-scares-me/

It is amusing to see regulatory agencies wrestling with ‘medical marihuana’ when it never would have gotten through the FDA given the few solid studies we have in man.

Why drug discovery is so hard: Reason #26 — We’re discovering new players all the time

Drug discovery is so very hard because we don’t understand the way cells and organisms work very well. We know some of the actors — DNA, proteins, lipids, enzymes but new ones are being discovered all the time (even among categories known for decades such as microRNAs).

Briefly microRNAs bind to messenger RNAs usually decreasing their stability so less protein is made from them (translated) by the ribosome. It’s more complicated than that (see later), but that’s not bad for a first pass.

Presently some 2,800 human microRNAs have been annotated. Many of them are promiscuous binding more than one type of mRNA. However the following paper more than doubled their number, finding some 3,707 new ones [ Proc. Natl. Acad. Sci. vol. 112 pp. E1106 – E1115 ’15 ]. How did they do it?

Simplicity itself. They just looked at samples of ‘short’ RNA sequences from 13 different tissue types. MicroRNAs are all under 30 nucleotides long (although their precursors are not). The reason that so few microRNAs have been found in the past 20 years is that cross-species conservation has been used as a criterion to discover them. The authors abandoned the criterion. How did they know that this stuff just wasn’t transcriptional chaff? Two enzymes (DROSHA, DICER) are involved in microRNA formation from larger precursors, and inhibiting them decreased the abundance of the ‘new’ RNAs, implying that they’d been processed by the enzymes rather than just being runoff from the transcriptional machinery. Further evidence is that of half were found associated with a protein called Argonaute which applies the microRNA to the mRBNA. 92% of the microRNAs were found in 10 or more samples. An incredible 23 billion sequenced reads were performed to find them.

If that isn’t complex enough for you, consider that we now know that microRNAs bind mRNAs everywhere, not just in the 3′ untranslated region (3′ UTR) — introns, exons. MicroRNAs also bind pseudogenes, SINEes, circular RNAs, nonCoding RNAs. So it’s a giant salad bowl of various RNAs binding each other affecting their stability and other functions. This may be echoes of prehistoric life before DNA arrived on the scene.

It’s early times, and the authors estimate that we have some 25,000 microRNAs in our genome — more than the number of protein genes.

As always, the Category “Molecular Biology Survival Guide” found on the left should fill in any gaps you may have.

One rather frightening thought; If, as Dawkins said, we are just large organisms designed to allow DNA to reproduce itself, is all our DNA, proteins, lipids etc, just a large chemical apparatus to allow our RNA to reproduce itself? Perhaps the primitive RNA world from which we are all supposed to have arisen, never left.

The dietary guidelines have been changed — what are the faithful to believe now ?

While we were in China dietary guidelines shifted. Cholesterol is no longer bad. Shades of Woody Allen and “Sleeper”. It’s life imitating art.

Sleeper is one of the great Woody Allen movies from the 70s. Woody plays Miles Monroe, the owner of (what else?) a health food store who through some medical mishap is frozen in nitrogen and is awakened 200 years later. He finds that scientific research has shown that cigarettes and fats are good for you. A McDonald’s restaurant is shown with a sign “Over 795 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 000 Served”

Seriously then, should you believe any dietary guidelines? In my opinion you shouldn’t. In particular I’d forget the guidelines for salt intake (unless you actually have high blood pressure in which case you should definitely limit your salt). People have been fighting over salt guidelines for decades, studies have been done and the results have been claimed to support both sides.

So what’s a body to do? Well here are 4 things which are pretty solid (which few docs would disagree with, myself included)

l. Don’t smoke
2. Don’t drink too much (over 2 drinks a day), or too little (no drinks). Study after study has shown that mortality is lowest with 1 – 2 drinks/day
3. Don’t get fat — by this I mean fat (Body Mass Index over 30) not overweight (Body Mass Index over 25). The mortality curve for BMI in this range is pretty flat. So eat whatever you want, it’s the quantities you must control.
4. Get some exercise — walking a few miles a week is incredibly much better than no exercise at all — it’s probably half as good as intense workouts — compared to doing nothing.

Not very sexy, but you’re very unlikely to find anyone telling you the opposite 50years from now.

It’s off topic, but I’d use the same degree of skepticism about the dire predictions of the Global Warming (AKA Climate change) people, particularly since there has been no change in global mean temperature this century.

The butterfly effect in cancer

Fans of Chaos know all about the butterfly, where a tiny change in air current produced by a butterfly’s wings in Brazil leads to a typhoon in Java. Could such a thing happen in cell biology? [ Proc. Natl. Acad. Sci. vol. 112 pp. 1131 – 1136 ’15 ] comes close.

The Cancer Genome Project has spent a ton of money looking at all the mutations of all our protein coding genes which occur in various types of cancers. It was criticized as we already knew that cancer is effectively a hypermutable state, and that it would just prove the obvious. Well it did, but it also showed us just what a formidable problem cancer actually is.

For instance [ Nature vol. 489 pp. 519 – 525 ’12 ] is report from the Cancer Genome Atlas of 178 cases of squamous cell cancer of the lung. There are a mean of 360 exonic mutations, 165 genomic rearrangements, and 323 copy number alterations per tumor. The technical details in the rest of the paragraph can be safely ignored but the point is that there no consistent pattern of mutation was found (except for p53 which is mutated in over 50% of all types of cancer, which we knew long before the Cancer Genome Atlas). Recurrent mutations were found in 11 genes. p53 was mutated in nearly all. Previously unreported loss of function mutations were seen in the class I major histocompatibility (HLA-A). Several pathways were altered relatively consistently (NFE2L2, KEAP1 in 34%, squamous differentiation genes in 44%, PI3K genes in 47% and CDKN2A and RB1 in 72%). EGFR and kRAS mutations are rare in squamous cell cancer of the lung (but quite common in adenocarcinoma). Alterations in FGFR are quite common in squamous cell carcinomas.

This sort of thing (which has been found in all the many types of tumors studied by the Cancer Genome Atlas) lead to a degree of hopelessness in looking for the holy grail of a single ‘driver mutation’ which leads to cancer with its attendant genomic instability.

All is not lost however.

MCF-10A is an immortalized epithelial cell line derived from human breast tissue. It is capable of continuous growth, but is far from normal: (1) an abnormal complement of chromosomes ) (2) threefold amplification of the MYC oncogene, and (3) deletion of a known tumor suppressor . It does lack some mutations found in breast cancer. For instance, the Epidermal Growth Factor Receptor 2 (ERRBB2) is not amplified. The cell line doesen’t express the estrogen and progesterone receptors — making it similar to triple negative breast cancer.

A single amino acid mutation (Arginine for Histidine at amino acid #1047 ) in the catalytic subunit of a very important protein kinase (p110alpha of the PIK3CA gene) was put into the MCF-10A cell line (which they call MCF-1A-H1047R). The mutation was chosen because it is one of the most frequently encountered cancer specific mutations known. Exome sequencing of the entire genome showed that this was the only change — but the control sequences outside the exons weren’t studied, a classic case of the protein centric style of molecular biology.

In the (admittedly not completely normal) cell line, the mutation produced a cellular reorganization that far exceeds the known signaling activities of PI3K. The proetins expressed were stimilar to the protein and RNA signatures of basal breast cancer. The changes far exceeded the known effects of PIK3CA signaling. The phosphoproteins of MCF-1A-H1047R are extremely different. Inhibitors of the kinase induce only a partial reversion to the normal phenotype.

They plan to study the epigenome. This is signifcant as breast cancers are said in the paper to have tons of mutations changing amino acids in proteins (4,000 per tumor). In my opinion they should do whole genome sequencing of MCF-A1-H1047R as well.

The mutant becomes fully transformed whan a second mutation (of KRAS, an oncogene) is put in. This allows them to form tumors in nude mice. Recall that nude mice (another rodent beloved of experimental biologists — see the previous post on the Naked Mole Rat) has a very limited immune system, allowing grafts of human cells to take root and proliferate.

How close the initial cell line is to normal is another matter. Work on a similar cell line the (3T3 fibroblast) has been criticized because that cell is so close to neoplastic. At least the mutant MCF-1A-H1047R cells aren’t truly neoplastic as they won’t produce tumors in nude mice. However, mutating just one more gene (KRAS) turns MCF-1A-H1047R malignant when transplanted.

The paper is also useful for showing how little we really understand about cause and effect in the cell. PI3K has been intensively studied for years because it is one of the major players telling cells to grow in size rather than divide. And yet “the mutation produced a cellular reorganization that far exceeds the known signaling activities of PI3K”

Time for drug chemists to hit the cell biology books

The (undeservedly) obscure Naked Mole Rat should be of interest to drug chemists for two reasons (1) it lives 8 times as long its fellow rodent the lab mouse (2) it never gets cancer (despite being under observation for the past 40 years). So untangling the mechanisms behind this should tell us about aging and cancer, particularly since cancer accounts for over 50% of the mortality in lab rodents. They age healthy. Until the last few years of their long lives, they show minimal morphological and physical changes of aging.

This post will concern a possible way Naked Mole Rats escape cancer. I’ve attempted to provide a molecular biologiocal background for chemists about DNA, RNA, gene transcription etc. See https://luysii.wordpress.com/2010/07/07/molecular-biology-survival-guide-for-chemists-i-dna-and-protein-coding-gene-structure/ and follow the links. There is very little in these posts about cell physiology and biology. I suggest having a look at “Molecular Biology of The Cell” and “Cancer” by Robert Weinberg. Get the latest editions, as things are moving rapidly.

The following paper tried to find out why Naked Mole Rats don’t get cancer [ Proc. Natl. Acad. Sci. vol. 112 pp. 1053 – 1058 ’15 ]. In tissue culture, naked mole rat fibroblasts show hypersensitivity to contact inhibition (aka early contact inhibition aka ECI). E.g. they stop dividing or die when they get too close to each other. The signal triggering ECI comes from hyaluronan (which has a very high molecular weight) outside the cell. Removal of high MW hyaluronan abrogates ECI and makes naked mole rat cells susceptible to malignant transformation.

ECI is associated with an increase in expression of p16^INK4a, a tumor suppressor (here is where the cell biology comes in). Cells losing expression no longer show ECI. Deletion and/or silencing of INK4a/b is found in human cancers as well. The genomic locus containing p16^INK4a is small (under 50 kiloBases), but it it codes for 3 different tumor suppressors (p16^INK4a, p15^INK4b and p14^ARF). The 3 proteins coordinate a signaling network depending on the activities of the retinoblastoma protein (RB) and p53 (more cell molecular biology).

In the naked mole rat, the INK4a/b locus codes for an additional product which consists of p15^INK4b exon #1 joined to p16^INK4a exons #2 and #3, due to alternative splicing. They call this pALT^INK4a/b. It is present in cultured cells from naked mole rat tissues, but is absent in human and mouse cells. pALT^INK4a/b expression is induced during early contact inhibition and by a variety of stresses such as ultraviolet light, gamma radiation, loss of substrate attachment and expression of oncogenes. When over expressed in human cells, pALT^INK4a/b has more ability to induce cell cycle arrest than either p16^INK4a or p15^INK4b. So pALT^INK4a/b might explain the increased resistance to tumors.

There’s also a lot of work concerning why they live so long, but that’s for another post.

Framingham shows us just how there is more to biology than genetics

If you have two copies of a particular variant (rs993609) of the FTO gene (FaT mass and Obesity associated gene) you are likely to weigh 7 pounds more then if you have neither. Pretty exciting stuff for the basic scientist, given the problems obesity causes (or at least is associated with). The study involved 39,000 people [ Science vol. 316 pp. 889 – 894 ’07 ]. At the end of the post, I’ll have a lot of technical stuff about just what FTO is thought to do inside the cell, but that’s not why I’m posting this.

Framingham Massachusetts is a town about 30 miles west of Boston. Thanks to the cooperation of its citizenry, it has taught us huge swaths of human biology since it began nearly 70 years ago. Briefly, The Framingham Health Study (FHS) was initiated in 1948 when 5,209 people were enrolled in the original cohort; since then, the study has come to be composed of four separate but related populations. The Framingham Offspring Study began in 1971, consisting of 5,124 individuals who represented the children of the original cohort population and their spouses. Participants in the offspring study were given physical examinations and detailed questionnaires at regular intervals starting in 1972, with a total of eight waves completed through 2008. The Body Mass Index (BMI) was calculated from measured height and weight. The offspring cohort was born over a 40-y period, with participants ranging in age from their teens to their late 50s at the time of study onset in 1971. In addition to providing survey and examination data, a large fraction of participants (73.0%, 3,742 individuals) had their DNA genotyped using the 100KAffymetrix array (43). Genotypes at the rs9939609 allele of FTO were extracted using PLINK (44) from data contained in the Framingham SHARe database.

Given the same gene, its effects should be constant through time, other things being equal. The following work [ Proc. Natl. Acad. Sci. vol. 112 pp. 354 – 359 ’15 ] mined the Framingham study to see if when you were born mattered to how fat you became if you carried the fat variant. There were 8 waves of data collection data from ’71 to ’08. Those born before ’42 showed less penetrance of the FTO gene.

Figure 1 p.356 is particularly impressive. Everyone became heavier as they got older. This is because height declines with age raising BMI even in the presence of constant weight. As far as I know, the following explanation from another post ( https://luysii.wordpress.com/2013/05/30/something-is-wrong-with-the-model-take-2/is original — “People lose height as they age, yet the BMI is quite sensitive to it (remember the denominator has height squared). The great thing about BMI is that it’s easily measured, and doesn’t rely on what people remember about their weight or their height. Well as a high school basketball player my height was 6′ 1”+, now (at age 75) its 6’0″. So even with constant weight my BMI goes up.

Well it’s time to do the calculation to see what a fairly common shrinkage from 73.5 inches to 72 would to to the BMI (at a constant weight). Surprisingly it is not trivial — (72/73.5) * (72/73.5) = .9596. So the divisor is 4% less meaning the BMI is 4% more, which is almost exactly what the low point on the curve does with each passing decade after 50 ! ! ! This might even be an original observation, and it would explain a lot.”

What is impressive about figure 1, is that those born before 1942 with two copies of the risk allele weren’t much heavier than those with one or no copies of the risk allele. This was true at all ages measured (remember these people were sequentially followed). Those born after 1942 carrying two copies of the high risk allele were 2 – 4 pounds heavier (again measured at all ages).

This is as good proof as one could hope for that environment affects gene expression, something we all assumed instinctively. There is no way one could repeat the experiment, except to start a new one in the future, which, as this shows, will occur in a different environment, which should make a difference. MDs gradually woke up to the fallacy of using historical rather than concurrent controls particularly in studies of therapies to prevent heart attack and stroke, as the rates of both dropped significantly in the past 50 years, and survival from individual heart attacks and strokes also improved.

So what does FTO actually do? Naturally anyone dealing with strokes wants to know as much as possible about one of the largest risk factors — obesity. What follows is a fairly undigested copy of my notes over the years on papers concerning FTO. I make no attempt to provide the relevant background, although most readers will have some. It’s interesting to see how our knowledge about FTO has grown over the years. Enjoy ! !

*****
[ Science vol. 316 p. 185, 889 – 894 ’07 ] FTO was first found in type II diabetics by looking for single nucleotide polymorphisms distinguishing 1924 UK type II diabetics from 2938 UK controls (were southeast Asians included?). Subsequently, larger populations (3757 type IIs and 5346 controls) were independently studied and the findings replicated. [ Cell vol. 134 p. 714 ’08 ] — The association hasn’t held up in the Han Chinese.

The FTO gene is found on chromosome #16. 16% of white adults have two copies of the variant (46% have one copy). They are 1.67 times more likely to be obese. At this point (13 Apr ’07) no one knows what the gene does.

FTO is a gene of unknown function in an unknown pathway that was originally cloned as a result of a fused-toe mutant mouse, that results from a 1.6 megaBase deletion of mouse chromosome #8. The deletion removes some 6 genes.

[ Cell vol. 131 p. 827 ’07 ] A blurb about something to be published in Science. This work shows that FTO codes for a nucleic acid demethylase. It has the enzymatic activity of a 2 oxo-glutaric acid oxygenase. The enzyme removes methyl groups from 3 methyl thymine (in DNA) 3 methyl uracil (in RNA). The SNPs linking FTO to obesity are in introns in the gene. In mice, the mRNA for FTO is highly enriched in the hypothalamus. Levels of FTO mRNA drop by 60% in fasting mice.

[ Science vol. 318 pp. 1469 – 1472 ’07 ] The Science paper at last. The gene produce catalyzes the Fe++ and 2-oxoglutaric acid dependent demethylation of 3 methyl thymine (which may not be the relevant substrate) in single stranded DNA with production of succinic acid, formaldehyde, and CO2. FTO is found in the nucleus in transfected cells. The mRNA for FTO is most abundant in the brain particularly in hypothalamic nuclei governing energy balance. FTO is inhibited by Krebs cycle intermediates (isn’t 2 oxoglutarate a Krebs cycle intermediate? ) particularly fumaric acid.

[ Science vol. 334 pp. 569 – 571 ’11 ] FTO removes methyl groups from 3 Methylthymine, and 3 methylUridine in single stranded DNA and RNA (ssDNA, ssRNA). The present work shows FTO converts 6 methylamino Adenine to adenine in RNA. FTO associates with speckles containing RNA splicing factors and RNA polymerase II

[ Nature vol. 457 p. 1095 ’09 ] Mice lacking FTO were normal at birth, but at 6 weeks weighed 30 – 40% less than normal mice (or haploinsufficients). This was due to loss of white fat — which was nearly completely absent at 15 months. The mutants ate more (in proportion to their body weight) than normal. On a high fat diet, both groups gained less weight than normals. Mice lacking FTO use more energy while not moving much.

[ Nature vol. 458 pp. 894 – 898 ’09 ] Loss of FTO in mice leads to postnatal growth retardation and a significant reduction both in fat and in lean body mass. The leanness is due to increased energy expenditure and sympathetic cativation, despite decreased sspontaneous motor activity and relative hyperphagia.

[ Proc. Natl. Acad. Sci. vol. 107 pp. 8404 – 8409 ’10 ] Carriers of the fat allele of FTO have smaller brains (8% smaller in the frontal lobes, 12% smaller in the occipital lobes). The brain differences weren’t due to differences in cholesterol, hypertension or white matter hyperintensities. So FTO risk isn’t a surrogate for the metabolic changes of obesity. The study was done in 206 cognitively normal adults (average age 76). Every 1 unit increase in BMI was assocaited with 1 – 1.5% reduction in brain volume in a variety of brain regions.

The highest expression of FTO is in the cerebral cortex. Whether expression in the hypothalamus changes after food deprivation is controversial.

It is known that obesity (BMI > 30) is associated with smaller brains. In this group temporal lobe atrophy was found in people with higher BMI but not in people with risk allele of FTO.

There was no effect of BMI on brain size in noncarriers of the FTO allele. So FTO status may influence the effect of BMI on the brain.

[ Cell vol. 149 pp. 1635 – 1646 ’12 ] A study of just what 6methylamino adenine (m6A) is doing and where in the genome it is doing it. m6A is the physiologically relevant target of FTO. It is found in tRNA, rRNA and mRNA. It fact m6A is found in 7,676 different mRNAs. The modification is markedly increased throughout brain development. m6A sites are enriched near stop codons and in 3′ untranslated regions (3′ UTRs). Even more interestingly, there is an association between m6A and microRNA binding sites in the 3′ UTRs ! ! ! m6A is not enriched at splice junctions. 30% of genes are said to have microRNA binding sites, but 67% of the 3′ UTRs containing m6A have microRNA binding sites. However, the two can’t overlap in the 3′ UTR. Many features of m6A localization are the same in man and mouse.

[ Nature vol. 490 pp. 267 – 272 ’12 ] In some way the SNP rs7202116 in FTO is associated with phenotypic variability per se. No other locus causes BMI variability this way.

[ Proc. Natl. Acad. Sci. vol. 110 pp. 2557 – 2562 ’13 ] FTO is widely expressed, with highest levels in brain, particularly the hypothalamus. FTO expression in the hypothalamus is decreased after a 48 hour fast, and incraeasing after a 10 week exposure to a high fat diet.

Carriers of the obesity promoting allele are hyperphagic and show altered (how?) macronutrient preference. This work shows that cells lacking FTO show decreased activation of the mTORC1 pathway, decreased rates of mRNA translation, and increased autophagy — all of which helps explain the stunted growth seen in man homozygous for FTO mutations.

FTO is rapidly degraded when cells are deprived of amino acids (this decreases TORC1 activity, making it a part of the physiological response to starvation). How this reoates to the demethylase activity of FTO isn’t known (yet). The methylase action is crucial for its ability to sustain mTORC1 activity in the face of amino acid deprivation.

[ Nature vol. 507 pp. 309 – 310, 371 – 375 ’14 ] Amazingly, the association between obesity and FTO involves another gene (IRX3) which is 500 kiloBases away. This was determined by chromosome conformation capture (CCC). The promoter of IRX3 interacts physically interacts with the first intron of FTO — this was found human cell lines, and other organisms. Obesity li9nked SNPs are associated with IRX3 expression in these samples, but not with expression of FTO. Mice lacking a functional copy of IRX3 have 25 – 30% lower body weight than controls (primarily due to loss of fat mass and increase in BMR with browning of white fat.

There is another case — an enhancer in an intron of LMBR1 reglates the developmental gene SHH found over a megaBase away. Mutations in the enhancer can cause limb malformations due to altered SHH expression.

Cancer as the telephone game

An interesting paper just out [ Science vol. 347 pp. 78 – 81 ’14 ] basically says that cancer is just bad luck due to copying errors of the 3.2 megaBase genome when cells divide. It’s a version of the telephone game in which a message is passed around a circle of people getting progressively garbled each time.

The evidence in support of the assertion is that the variation in cancer rates between tissues is strongly related to the number of divisions of the stem cells required to maintain that tissue. For instance the lifetime risk of being diagnosed with cancer is 7% for lung but .6% for brain (about this more later). Risk in the GI tract varies by a factor of 24 (.5% for the esophagus 4.8% for the colon) which is proportional to the number of stem cell divisions undergone during lifetime.

They estimate that at most 1/3 of the variation in risk among tissues is due to environmental factors or inherited predisposition. That’s certainly not to say that you should go ahead and smoke.

The idea makes a lot of sense. Even though the error rate in copying the parental genome to a child is an amazingly low 1/100,000,000 that still is 32 mutations per generation (more from the father than the mother and more from him the older he is, not so for the mother)– for details please see https://luysii.wordpress.com/2012/08/30/how-fast-is-your-biological-clock-ticking-ii-latest-results/.

There is even better evidence for this based on my clinical experience in neurology for 35+ years. The lifetime chance of a brain tumor is stated to be .6%. However in all these years I never saw a brain tumor made of neurons. They were all derived from glia (astrocytoma, glioblastoma) or the coverings of the brain (meningiomas). Why? Essentially neurons in the cerebral cortex (not the deeper parts of the brain) don’t divide. [ Cell vol. 153 pp. 1183 – 1185, 1219 – 1227 ’13, Science vol. 340 pp. 1180 – 1181 ’13 (Editorial) ] Even the parts that do divide add a trivial amount of neurons to the brain (700 neurons a day). Even if you live 100 years — that’s only 100 * 365 * 700 == 26 million neurons, a trivial amount compared to the 100 billion neurons you are estimated to have (this number grows each time I read about it).

You might be interested in how we can make statements like this about new neuron formation in the brain. It’s very clever — Carbon-14 accumulated in the atmosphere between the mid 50s and early 60s as a byproduct of above ground testing of nuclear weapons. Such testing was banned by treaty in 1963 and carbon-14 levels in the atmosphere declined in the following decades to previous low background levels. Carbon-14 is used in archeologic dating because its halflife is 5730 years.

Using postmortem tissue samples of individuals born before and after the nuclear bomb tests, the integration of carbon-14 into genomic DNA was measured. This would have occurred during the cell’s last division cycle. One can calculate the birth dates of different cell types collected from various tissues including brain. The approach is accurate to within a few years. The 5730 year half life of 14-C means that whatever is in human DNA hasn’t had a chance to decay (by much) in 50 years. The amount of carbon-14 in cellular DNA therefore reflects the amount of carbon-14 in the atmosphere when the cells underwent their last division. The amount of carbon-14 in the atmosphere was determined by measuring it in the annual growth rings of pine trees in Sweden — a surrogate for atmospheric carbon-14 levels in the past 60 years. The birthdate of cells is determined as the year the C-14 in them matches those of the pine trees.

Microexons, great new drugable targets

Some very serious new players in cellular and tissue molecular biology have just been found. They are very juicy drugable targets, not that targeting them will be easy. If you don’t know what introns, exons and alternate splicing are, it’s time to learn. Go to https://luysii.wordpress.com/2010/07/07/molecular-biology-survival-guide-for-chemists-i-dna-and-protein-coding-gene-structure/ read and follow the links forward. It should be all you need to comprehend the following.

The work came out at the tail end of 2014 [ Cell vol. 159 pp. 1488 – 1489, 1511 -1523 ’14 ]. Microexons are defined as exons containing 50 nucleotides or less (the paper says 3 – 27 nucleotides). They have been overlooked, partially because their short length makes them computationally difficult to find. Also few bothered to look for them as they were thought to be unfavorable for splicing because they were too short to contain exonic splicing enhancers. They are so short that it was thought that the splicing machinery (which is huge) couldn’t physically assemble at both the 3′ and 5′ splice sites. So much for theory, they’re out there.

What is a cell and tissue differentially regulated alternative splicing event? It’s the way a given mRNA can be spliced together one way in tissue/cell #1 and another in tissue/cell #2 producing different proteins in each. Exons subject to tissue specific alternative splicing are significantly UNDERrepresented in well folded domains in proteins. Instead they are found in regions of protein disorder more frequently than one would expect by chance. Typically these regions are on the protein surface. The paper found that the microexons code for short amino acid motifs which typically interact with other proteins and ligands. 3 – 27 nucleotides lets you only code for 1 – 9 amino acids.

One well known example of a short interaction motif is RGD (for Arginine Glycine Aspartic acid in the single letter amino acid code). The sequence is found in a family of surface proteins (the integrins) with at least 26 known members. These 3 amino acids are all that is needed for the interns to bind to a variety of extracellular molecules — collagen, fibrin, glycosaminoglycans, proteoglycans. So a 3 amino acid sequence on the surface of a protein can do quite a bit.

Among a set of analyzed neural specific exons (e. g. they were only spliced that way in the brain) found in known disordered regions of the parent protein, 1/3 promoted or disrupted interactions with partner proteins. So regulated exon splicing might specify tissue and cell type specific protein interaction networks (Translation: they might explain why tissues look different even when they express the same genes). The authors regard microExon inclusion/exclusion as protein surface microsurgery.

The paper has found HUNDREDS of evolutionarily highly conserved microexons from RNA-Seq data sets (http://en.wikipedia.org/wiki/RNA-Seq) in various species. Many of them impact neurogenesis and brain function. Regulation of microExons changes significantly during neuronal differentiation. Although microexons represent only 1% of the alternate splice sites seen, they constitute ‘up to’ 1/3 of all evolutionarily conserved neural-regulated alternative splicing between man and mouse.

The inclusion in the final transcript of most identified neural microExons is regulated by a brain specific factor nSR100 (neural specific SR related protein of 100 kiloDaltons)/SRRM4 which binds to intronic enhancer UGC motifs close to the 3′ splice sites, resulting in their inclusion. They are ‘enhanced’ by tissue specific RBFox proteins. nSR100 is reduced in Autism Spectrum DIsorder (really? all? some?). nSR100 is strongly coexpressed in the developing human brain in a gene network module M2 which is enriched for rare de novo ASD assciated mutations.

MicroExons are enriched for lengths which are multiples of 3 nucleotides (implying strong selection pressure to preserve reading frames). The microExons are also enriched in charged amino acids. Most microExons show high inclusion at late stages of neuronal differentiation in genes associated with axon and synapse function. A neural specific microExon in Protrudin/Zfyve27 increases its interaction with Vesicle Associated membrane protein associated Protein VAP) and to promote neurite outgrowth. A 6 nucleotide neural microExon in Apbb1/Fe65 promotes an interaction with Kat5/Tip60. Apbb1 is an adaptor protein functioning in neurite outgrowth.

So inclusion/exclusion of microExons can alter the interactions of proteins involved in neurogenesis. Misregulation of neural specific microexons has been found in autism spectrum disorder (what hasn’t? Pardon the cynicism).

Protein interaction domains haven’t been studied to nearly the extent they need to be, and we know far less about them than we should. All the large molecular machines of the cell (ribosome, mediator, spliceosome, mitochondrial respiratory chain) involve large numbers of proteins interacting with each other not by the covalent bonds beloved by organic chemists, but by much weaker forces (van der Waals,charge attraction, hydrophobic entropic forces etc. etc.).

Designing drugs to interfere (or promote) such interactions will be tricky, yet they should have profound effects on cellular and organismal physiology. Off target effects are almost certain to occur (particularly since we know so little about the partners of a given motif). Showing how potentially useful such a drug can be, a small molecule inhibitor of the interaction of the AIDs virus capsid protein with two cellular proteins (CPSF6, TNPO3) it must interact with to get into the nucleus has been developed. (Unfortunately I’ve lost the reference)

My cousin married a high school dropout a few years ago. Not to worry — he dropped out of high school to go to college, and has a PhD in Electrical Engineering from Berkeley and has worked at Bell labs. He was very interested in combining his math and modeling skills with my knowledge of neurology to make some models of CNS function. I demurred, as I thought we knew too little about the brain to come up with models (which I generally distrust anyway). The basic problem was that I felt we didn’t know all the players in the brain and how they fit together.

MicroExons show this in spades.

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