The Boy Who Wasn't Short

by Kirk, Edwin;

  [5 A similar compound, ethylene glycol, is used as antifreeze in car radiators, and is also poisonous.]

  In 1960, Kelsey was offered a job at the FDA. The very first task she was given was to review the application for approval of thalidomide. The drug had been used in Germany since 1957 and had rapidly spread through the world after that; it was generally believed to be safe. Kelsey was given the job of reviewing this particular application because it was thought a good idea to give new employees a relatively easy assignment to start with(!). Fortunately for thousands of American children, Kelsey’s training, experience, rigorous approach to the evidence presented, and refusal to be intimidated by the drug company (which put enormous pressure on her to relent), all made her ideally suited to assess this particular application.

  For once, the rest of this story is not that of an unsung hero whose work was disregarded during their lifetime. Kelsey received the credit she richly deserved. The Washington Post ran a front-page story entitled ‘“Heroine” of FDA Keeps Bad Drug Off of Market’. In 1962, President John F. Kennedy presented her with the President’s Award for Distinguished Federal Civilian Service, the highest honour the US government gives to its civilian employees. In 2000, she was inducted into the National Women’s Hall of Fame. She retired in 2005, aged 90. In 2010, she received the FDA’s inaugural Drug Safety Excellence Award, which was named after her and is given annually to an FDA employee. Kelsey died in Canada in 2015, aged 101, shortly after being presented the Order of Canada by the Canadian governor-general.

  By contrast … I know this is probably unfair on her, given that I am writing from a position of hindsight, but I can’t resist telling you about a letter written to the British Medical Journal by one Paula H. Gosling, published on 16 December 1961. It is a nice example of a longstanding tradition of medical resistance to change. Gosling roundly criticises the decision to withdraw the drug from sale. ‘I must protest against the action of the Distillers Company in withdrawing … thalidomide … from the market’, she says, and then argues that, if this had been done because of the reports of nerve damage, that would have been one thing, but ‘to do so on the grounds of two unconfirmed reports from alien sources of a possible — not proved — association of thalidomide given in early pregnancy is quite irresponsible’. Charmingly, she goes on to point out that because thalidomide is tasteless and odourless, it is the ideal sedative for children … and cats! Lastly, she suggests that ‘any doctor alarmed by these unconfirmed reports’ could prescribe other drugs ‘for pregnant females’ … and concludes, ‘Have we lost all sense of proportion?’

  No doubt Gosling came to regret this letter before much time had passed.6

  [6 In fairness, I should confess that I have done something rather similar. I wrote a testy letter to the journal Nature, following the early reports that babies whose mothers were infected by zika virus during pregnancy could suffer damage to their brains, causing them to be born with small heads and go on to have neurological problems. The letter mainly complained about sloppy use of terminology, but also pointed out that, so far, there wasn’t really a lot of hard evidence for harmful effects from zika infection. Within a week of its publication, a paper came out in The New England Journal of Medicine that nailed down the relationship, beyond any reasonable doubt. I had vigorously and thoroughly plastered my face with egg, while standing on the most visible platform in science.]

  If a drug that is taken during pregnancy causes malformations in the baby, it is called a teratogen.7 Thalidomide is one of the most potent teratogens known — even a single tablet, taken at the wrong time, can have devastating effects. And yet … and yet there were babies whose mothers took thalidomide during the critical time in early pregnancy, when the fetus is most sensitive to its ill effects, and were nonetheless born whole, hale and hearty, somehow unharmed. Very likely, the babies born unscathed by their exposure to thalidomide were a small minority — but there is good evidence that they exist. How could this be?

  [7 The word derives, rather unfortunately, from a Greek word meaning ‘monster’. Medications are only one type of teratogen — other drugs, such as alcohol, and maternal infections, such as zika, can also be teratogens.]

  *

  A few times a year, I give a lecture to medical students about genetics. The idea is to give them an overview of the role of genetics in medicine, reminding them of the fundamental principles they were meant to have learned earlier in the course, and trying to give them a feel for where the field is going. If you’re a medical student today, it’s pretty much guaranteed that some of your future patients will be having genetic tests, and, if you’re going to order a test and receive a report, it helps to have some idea of what the results might mean. Anne Turner used to give the same lecture, which she called ‘genetics in an hour’, and, in the years since I took it over, I find myself constantly realising that some new development should be added, then discovering that the lecture is too long and deleting slides.

  Even so, I always take time to make the case that each and every other branch of medicine should be viewed as just a subspecialty of genetics. Pretty much everything that afflicts human beings, and everything about us that is not an affliction, too, has genetics at its core.

  Take trauma, for instance. You may not think that being involved in a car accident, or getting punched, is a genetic problem. Consider, though, that there is a major genetic risk factor that strongly influences whether these things will happen to you. It is called the Y chromosome. At every age after 12 months — the age at which most of us are able to get up, about, and into mischief — males are more likely to be injured than females.

  You may have some thoughts about why this should be the case. The obvious culprit is testosterone: aggressiveness and impulsiveness are characteristics that will put you in harm’s way, and testosterone is known to promote both.

  That may well be a contributing factor, but most likely it’s not as simple as that — there are probably other ways that the Y chromosome influences behaviour. Of course (despite my desire to put genetics at the centre of the medical universe), we should not imagine that the differences in behaviour between men and women are due only to their different and inborn physical and chemical make-up. There are social as well as genetic influences on maleness and the way that men behave. If you are conditioned from birth to think that you should be adventurous and bold, nobody should be very surprised if you do wind up adventurous and bold. If you’re taught that your place is in the home, and that quiet, passive pursuits will suit you best — well, you might cut loose, but, on the whole, there’s a decent chance that this upbringing will affect your choices in life, in ways that tend to keep you out of harm’s way.

  Yet to muddy the waters still more, there are other genetic influences on your chance of getting hurt, whether or not you are encumbered by a Y chromosome. Not all men have the same risk of getting hurt as each other, and there is plenty of overlap in behaviour (and risk) between men and women. Both men and women can be more or less impulsive; some men (and women) are more likely to stay home and play video games, while others prefer to go out BASE-jumping. Those differences between members of the same sex are also under genetic control to some degree, but understanding them is not as simple as being able to point at a single errant chromosome and blame that.

  In short, the genetics of trauma are complex, and there is an interplay between genes and environment. That balance is not always the same, and there are times when environment can completely overrule genetics. Put the most peaceable, unadventurous woman in Baghdad and she may, by sheer bad luck, be at the market when a car bomb explodes. Put the most (potentially) reckless and aggressive of men in an environment where men are socialised against violence and other opportunities for harm are limited (you’ll note that I couldn’t think of a good example of such an environment, but all things are relative) and he may live, unscathed by any violence, to a ripe old age and then die in his
sleep.

  This type of interaction between genes and environment has an effect that is easiest to study and understand in a population, rather than at the level of a single individual. It’s a bit like the difference between climate and weather: we know that, on average, men are more likely to experience violence, just as we know that, on average, it’s hotter in summer than in autumn. Nonetheless, it’s not terribly surprising for there to be a cool day in summer or a warm day in autumn; the individual days are like individual people. Just as we can’t predict what the weather will be like a year from today, even perfect knowledge of a baby’s genetic make-up will never tell us exactly what type of person they will become, or even exactly what kind of health problems they may experience.

  Virtually all human diseases have some contribution from genes. This ranges from conditions like those that mostly fill this book — in which a single gene is faulty or there is a problem at the level of a chromosome, and that is enough on its own to cause a genetic condition — through to common conditions like stroke, in which genes and environment are both important, and the genetic contribution is not from a single gene but from many. That latter scenario involves many, many different genetic elements, each of which gives a tiny nudge to the chance that you will have a stroke. Some nudge your risk up, some nudge it down. It’s likely that there are hundreds or even thousands of such genetic nudges acting on the risk for each common medical condition; for most people, most of the time, any one of these only has a very small effect. A genetic variation that increased or decreased your chance of having a stroke by 20 per cent would be considered to have a very strong effect. A catalogue of genetic influences on stroke8 identified 287 different places where there was good evidence for such a nudge, most of which only have only a slight impact on risk.

  [8 Part of a catalogue kept by the National Institutes of Health, accessible at https://www.ebi.ac.uk/gwas/home]

  The main way that we have identified genetic influences on common disease, so far at least, is through genome-wide association studies (GWAS). If you want to run a GWAS,9 you need very large numbers of people — tens to hundreds of thousands10 — about whom you know something. Perhaps you know how tall they are, or what their blood pressure is, or whether they have had a stroke. You get DNA from each of them and look at thousands of places, spread across the genome, where there is known variation between people. Then you compare these genetic results with the known information about the people in your study. The aim is to find a link between the DNA results and the characteristic you are studying.

  [9 Personally, I have no desire to do this, but I won’t judge you if you decide to give it a go.]

  [10 Putting together data from such large numbers of people often requires huge collaborations. In 2014, a study of the genetics of height published in the journal Nature Genetics had 445 authors, as well as four groups who were not individually named. Yes, I counted them.]

  Suppose there is a particular spot where some people have a C whereas others have a T. When we look at people who have not had a stroke, we find that 50 per cent have a C and 50 per cent have a T. Then we look at people who have had a stroke, and find that 60 per cent have a C and 40 per cent have a T. People with stroke are more likely to have a C than the controls.11 The next step is to do the study all over again, in a ‘replication cohort’ — a second group of people — to demonstrate that the link you found the first time around wasn’t a fluke. This is necessary because, in the early days of GWAS, there were numerous GWAS ‘hits’ that turned out to be statistical blips with no relationship to reality. The statistical bar for that second study is a bit lower than for the first, because you’re looking at one particular target rather than scanning the whole genome. This means you don’t need quite as many people in your second group, but it’s still a lot of work. Let’s say that, second time around, you find something similar to your original result. Congratulations, you’ve found a risk factor for stroke!

  [11 If the numbers had been the other way round, C would have been protective against stroke rather than a risk factor.]

  … but it may not help you all that much. For a start, it may well be that this genetic difference does not, of itself, have any direct bearing on the risk of stroke. It could be an innocent bystander that just happens to be sitting, minding its own business, somewhere close to some other change that is the actual culprit. This means that identifying a variant like this is often only the first part of a long and frustrating search for the actual villain in the piece. The second problem is that the information is pretty meaningless for any one person. If half of the population have a C, and there’s only a small extra risk of stroke in people who have a C, you shouldn’t get too worried if you find that you have it, too. And the information may not be meaningful for people from a different population — the link between this particular C and stroke might only hold true in people from a European background, for example. There is an unfortunate oversupply of studies done in people with European ancestry, unfortunate because of the serious lack of similar studies in people from other populations.

  There is a pretty good chance that your GWAS hit does not sit inside an actual gene. Most do not. Sometimes that’s because of the innocent-bystander phenomenon mentioned above — there is a change in a gene that’s important, and the C that you found is sitting near that change. More often, though, if we can find a specific reason why a particular variant is associated with a condition we’re interested in, it relates to how genes are controlled, rather than to changes that result in a different version of a protein being produced. The genome is full of sequences that are important for regulating activity in the cell nucleus. This often works by producing signals in the form of RNA, a chemical that is nearly-but-not-quite the same as DNA. This activates that, which suppresses the other thing, which in turn changes the activity of a gene, meaning more or less of a protein being produced … which might be relevant to the thing you were interested in to begin with. Our understanding of this network of signals is far from complete, but it’s likely that many GWAS hits involve subtle shifts of balance in a tangled web of information — not something we are likely to figure out in a hurry.

  Ideally, we would like to identify all of the genetic variation that affects human12 diseases, as well as characteristics like height. If we could completely understand the genetic influences that decide whether a particular person will have a heart attack, it might be possible to find new ways of preventing that from happening.

  [12 My focus in this book is on humans, but the same technology is widely used in other organisms, including for the purposes of agriculture. If you can identify genetic variation that influences milk production in cows, the dairy industry will beat a path to your door. There are plenty of similar applications in other areas, from crop production to horse racing — and it goes beyond the more obvious organisms. For some years, until he retired, I collaborated with Professor Chris Moran at the University of Sydney. Chris was part of the team that sequenced the genome of the saltwater crocodile, and he worked on finding variation that affected the speed at which young crocodiles grow, as well as characteristics of their skin that are important in crocodile-leather production. Virtually every economically important organism — from honey bees to rice to farmed salmon — has had its genome studied in an effort to figure out how to make them more productive, and lucrative.]

  Long before the human genome was sequenced, there were efforts to figure out how important genes are in controlling various conditions and characteristics. Think ‘nature vs nurture’, with an effort to actually measure the ‘nature’ part. A widely used measure in this area is heritability — the degree to which variation in a particular characteristic within a population is due to genes rather than environment. The name makes it sound like this is a direct measure of the ‘nature’ part of the equation, but that’s not quite right: it really is about variability within the population. To illustrate this point, ima
gine you are studying hair colour in two different groups. One group is composed entirely of Nigerians; the other is composed of a random sampling of Brazilians. The Nigerians all have black hair, so there is no variation to measure: heritability will be zero. That doesn’t mean genes aren’t important in controlling the hair colour of Nigerians — quite the opposite is true. The Brazilians have everything from black hair to blonde. This variability is mostly explained by genetics, so heritability will be high.

  There are several ways of calculating heritability. A common and relatively simple approach is to compare the degree to which identical and non-identical twins are similar. The assumption is that twins share their environment equally, even down to the conditions they experience while still in the womb, and that environmental effects are no different for identical and non-identical twins. Since identical twins share all of their genes,13 whereas non-identical twins share, on average, only half of their genes, you expect (and usually observe) that identical twins will be more similar to each other than non-identical twins — not just in physical appearance but also in height, blood pressure, and so on. Some fairly simple maths, by the standard of this sort of thing, lets you measure that difference across a group of twins, and use it to calculate heritability. Heritability scores, however calculated, range from zero (no contribution from genes to the variation in that population) to one (the variation is entirely due to genetics); they can also be expressed as percentages.

  [13 In principle. In fact, it is possible for identical twins to have differences either in the sequence of their genes (that happened after the split, and that would usually be mosaic) or in some of the settings within the cells that control the functioning of genes. Usually, these are too subtle to cause differences that you can observe just by looking at them, but they are real nonetheless.]