The Boy Who Wasn't Short

by Kirk, Edwin;

  Heritability estimates for different characteristics vary between studies, and between populations. One measure that is relatively consistent across a number of studies has been height: in well-fed populations, height has a heritability of 0.8. Most of the variation in height is due to genetic effects. Studies in China have found lower heritability for height, around 0.65. That’s still an important contribution from genes, but suggests that environment might be more important in China than in, say, the US. A possible explanation for this relates to the fact that, if your mother is undernourished while you are in the womb, and you are undernourished as a child, you are likely to wind up shorter than you would have done otherwise. Study people who have grown up in hard times and you will see a larger impact from the environment, pushing the contribution from genes down.

  GWAS became possible in the mid-2000s, and really took off in about 2007. Pretty quickly, the GWAS-ologists became aware of an awkward problem: missing heritability. By 2010, after quite a bit of effort, GWAS studies had managed to explain only 5 per cent of the variation in height — quite a gap from the 80 per cent predicted by measures of heritability! Gradually, over the past decade and a bit, that gap has narrowed — but there is still a gap and it’s not fully explained. The biggest study of the genetics of height so far used data from nearly half a million people from the United Kingdom, volunteers who had donated DNA and extensive personal and medical information as part of the UK Biobank project. A group led by Stephen Hsu (our second Hsu — of whom more later) was able to use this treasure trove of data to explain 40 per cent of the variation in height — an impressive feat, but far from allowing us to predict someone’s height accurately from their DNA alone. The predictive score they developed allowed them to estimate the heights of most of a group of people (not part of the original data set) to within a few centimetres. That sounds impressive, but the range of possible actual heights for any given predicted height was pretty wide. Imagine a witness in a court case saying, ‘I think the man was about five foot eight, give or take an inch or two. But he could have been as short as five foot two or as tall as six foot two.’14 Hsu’s group also convincingly showed that, for height, studying more people or looking at more genetic markers would be unlikely to provide more accuracy — they have taken this approach about as far as it is ever likely to go. They also looked at educational attainment, measured on a six-point scale that tops out at ‘university degree’, and found they could explain just 9 per cent of the variation in that measure, but also that an even more enormous study would have a decent chance of explaining more of the variation.

  [14 Or, if you prefer metric, ‘I think the man was about 173 cm tall, give or take a few centimetres, but he could have been as short as 157 cm or as tall as 188 cm.’]

  Why is it that even a superb study, using huge amounts of data, can only explain part of the variation that should be there to find? There are two main explanations that are put forward. The first argues that the traditional measures of heritability are substantial overestimates — for example, a recent study using data from Iceland and incorporating genetic data (from whole genome sequencing) in calculating heritability found rather lower values than from the traditional approaches. For height, rather than heritability of 0.8, the new estimate was only 0.55 — suggesting that Hsu’s group found more than 70 per cent of all that there was to find. For body mass index (BMI),15 the numbers were 0.65 (old method) and 0.29 (new method); for educational attainment, it was 0.43 and 0.17 — both very substantial differences.

  [15 A measure of the relationship between height and weight; it is weight in kilograms, divided by height in metres squared.]

  Perhaps more interestingly than just a miscalculation, an alternate explanation for missing heritability is that there are huge numbers of undiscovered genetic contributors to the characteristics that are being studied — but most of them only have very, very tiny effects, that are too hard to measure even if very large numbers of people are studied. This idea is not new — its centenary was in 2018. In 1918, R.A. Fisher, one of the luminaries of modern statistics, proposed the infinitesimal model, in which a variable characteristic like height is under the control of an infinitely large number of genes, each of which has an infinitely small impact on the characteristic, as well as, of course, environmental influences. Fisher wasn’t suggesting there really are an infinite number of genes, it was just a way of thinking about the problem.

  It’s possible you haven’t heard of Fisher, but in certain circles he remains a revered figure. This is not so much for the infinitesimal model — a relatively minor achievement by his standards — but for many other major contributions to statistical and genetic theory. Ian Martin, the scientist who taught me how to breed mice,16 retired a few years ago. In December 2016, the University of Sydney honoured Ian’s contributions to the field of mouse genetics, and to the university, by awarding him an honorary doctorate in veterinary science. At a reception held before the ceremony, Ian told me in detail about the time that he met Fisher and showed him some of his work, which Fisher commented on favourably. Ian was awarded his PhD in 1962, the year that Fisher died, so the events must have occurred well over half a century before, but it was obvious that their encounter was as clear in Ian’s mind as though it had happened the previous week. I was deeply impressed to hear that my friend and teacher had known the great man.17

  [16 For scientific purposes, not as a hobby.]

  [17 I wish I could say that Fisher’s reputation is as a giant of statistics and nothing else. Unfortunately, his reputation is somewhat blemished by his membership of the Eugenics Society at Cambridge, and by his firmly held views that there are real and important differences between the races of humans. A small positive of this, for me at least, is that through Fisher I am connected in a surprisingly small number of steps to Charles Darwin. I know Ian Martin, who met Fisher, who knew Horace Darwin — a fellow member of the Eugenics Society, and son of Charles Darwin. That’s just four degrees of separation. From Darwin!]

  Let us drag ourselves reluctantly from scientific hero-worship to look at ‘environment’ a bit more. If the potential environmental influence on your health is a speeding truck, it’s fairly obvious. If it’s an infectious disease, you might be tempted to think not only that the environmental component (the virus, bacterium, fungus, or parasite) is obvious, but that it’s the only thing that matters. If so, you’d be wrong. Some people have immune systems that deal well (or poorly) with particular types of infection. At one extreme, there are people who are almost immune to infection by HIV, as we’ve seen (in chapter 8). At the other are people with genetic immune deficiencies, whose bodies are terribly vulnerable to some types of infection, or to any infection at all. All the rest of us lie somewhere in between those extremes, along a spectrum of susceptibility.

  There’s an interaction between host and infection, and not all germs are created equal, so that both sides of this equation are variable. Someone who is naturally resistant to influenza encounters a mild strain of the flu and doesn’t even notice that they are ill. Someone else, with an average immune system, encounters a flu virus that is average in nastiness, and has a miserable few days but recovers with no lasting effects. And someone with a vulnerable immune system has the bad luck to run into a particularly gnarly virus … like the H1N1 strain that rampaged across the world in 1918 (Spanish flu) and 2009 (swine flu) … and that person dies.

  In genetics, a particular focus of our thinking about the interaction between genes and environment is the early months of pregnancy. Thalidomide is an extreme and infamous example of an environmental influence on early development, but there are other medicines that are known to have the potential to harm the unborn baby. Isotretinoin, marketed as Accutane or Roaccutane, is very effective at treating acne. Unfortunately, if a woman becomes pregnant while taking this drug, there is a very high risk of a variety of problems in the baby — physical malformations and intellectual disabi
lity — although many babies are unharmed. Some drugs that are used to treat epilepsy can cause problems for the baby as well, which can lead to a difficult choice in women who have severe epilepsy and need to take a drug that is risky to use in pregnancy. Do you accept the risk to the child or switch drugs, knowing the mother might have seizures, which come with their own problems?

  It’s not just medications that can potentially hurt the developing baby. Alcohol can cause significant harm, particularly to the brain. Most of the evidence for this comes from the children of mothers who have consumed large quantities of alcohol for a large part of the pregnancy, but it’s not clear whether there is any truly safe amount of alcohol to consume, so the advice that’s given to pregnant women is appropriately cautious. Smoking during pregnancy can cause miscarriage, or poor growth during the pregnancy, among other problems. There are infections that are serious problems — the main reason we vaccinate against rubella is to prevent infections during pregnancy, and there are plenty of other infections which are bad news for the baby (zika virus is a recent addition to the list). The babies of mothers who are diabetics are more likely to have a range of physical malformations; this isn’t a problem for women with the version of diabetes that is caused by pregnancy (gestational diabetes), because, by the time this problem starts, the growing fetus is fully formed. Not that gestational diabetes is harmless — far from it: it carries significant risks to mother and child, but physical malformations in the baby are not among them.

  All these hazards are real, but they all share the characteristic of unpredictability. You can’t be sure — even with thalidomide — exactly what will happen in a pregnancy. There’s also the problem that, for many medications, there just isn’t much evidence about risks in pregnancy; this has led to the development of efforts to study and monitor the outcomes in babies whose mothers took any kind of medication during pregnancy.

  We don’t have a full understanding of why some babies are badly affected by a particular insult, while others suffer no harm, but there’s good reason to think that genetic variation is involved. That could be variation that directly protects the baby — perhaps that baby’s genes that give the instructions to make arms and legs, and to keep the blood flowing to the growing limbs, are particularly robust versions. Or it could be maternal genetic factors that protect the baby. Perhaps the mother has a genetic variant that means that her gut absorbs thalidomide poorly, so that levels in her blood never get high enough to matter.

  On the whole, public awareness that the mother’s actions can sometimes harm her baby is a good thing. It leads women to stop smoking and avoid alcohol during pregnancy, and to be careful about the medications they take. But like many things, this knowledge can be a two-edged sword. I once saw a man in his early 40s, Barry, who had intellectual disability. He could walk, and talk a little, but was dependent on his parents for most things. His younger sister, in her 30s, was pregnant and was concerned that her child might also have intellectual disability. Efforts to make a diagnosis had been unsuccessful back when Barry was a child, in the 1970s, and nobody had tried since then. After a while, the question seemed less important to those who cared for him than managing his day-to-day health problems. Finally, though, Barry’s sister asked the question again. When I saw Barry, I suspected a chromosomal problem, and so it proved when I tested him — he had a chunk missing from one of his chromosomes that was undoubtedly the cause of his problems.

  The news had a profound impact on his mother, a woman in her late 60s. While pregnant with Barry, her first child, she had painted the nursery; after his problems manifested, she became convinced that she had absorbed fumes from the paint that had damaged her baby’s brain. She believed that Barry’s problems were entirely her fault. For decades, she had carried this needless burden of guilt; it had eaten away at her for all that time. The chromosome result lifted the burden from her. Like others I’ve seen in this situation, her emotions were powerful and complex; relief that she was not at fault, mixed with sadness for the years she had spent believing that she was.

  Asking about events during pregnancy is an important part of a clinical genetics consultation, because occasionally there can be important clues about the cause of the problem. But even when it’s obvious that nothing that happened was relevant to the child’s problem, I try to remember always to ask the parents if there is something that happened that they are worried about, because people don’t always volunteer the information. For many years, I was part of the clinic at Sydney Children’s Hospital that looks after children with clefts of their palates, lips, or both. A cleft is a split, usually caused by a failure of separate parts to join up as they should during early development. Sometimes, I would see children who had an underlying genetic condition, be that chromosomal (like velocardiofacial syndrome) or some other syndrome that was the cause of the cleft. But most children at the clinic are perfectly healthy apart from their cleft, and, thanks to the excellence of modern plastic surgery, they generally do very well once the cleft is repaired, with surprisingly subtle scars for those with cleft lips.

  Their parents still want to know why this happened, and whether it was their fault. Often, the most useful thing I did in that clinic was taking explanations away from people, rather than the opposite. No, the stress you were under at work was not the cause of the cleft, and nor were those antibiotics you took, or the toner you got all over your hands that time that the printer at work went berserk.

  Although we can’t usually point to a specific cause of conditions like cleft palate or congenital heart disease, we can have a decent crack at working out how important genetic factors are in causing them. For both of these conditions, we know that there are some families in which a change in a single gene is the main cause of the problem. I’ve contributed in a small way18 to identifying single-gene causes of congenital heart disease, and my friend Tony Roscioli (who is a genetic Sherlock Holmes, with an extraordinary capacity to sift through genetic data and uncover new links between genes and diseases) has found several genes linked to cleft palate. But even for ‘single-gene’ conditions, the outcomes are unpredictable — one child in a family might be born with a heart so scrambled that it is beyond repair, whereas another, despite having the same genetic variant, might have a minor problem, or even a completely normal heart. In this setting, an important part of the environment is something unexpected: it’s luck.

  [18 As a minor player in a cardiac genetics group led by two embryologists, Sally Dunwoodie and Richard Harvey, and a cardiac surgeon, David Winlaw — powerhouses all.]

  It may seem like a cop-out to say, ‘This child had a genetic variant that might have been fatal, but was lucky and suffered little harm, whereas this other child was unlucky and died.’ But there’s a solid scientific basis to this idea. At the scale of a single molecule of DNA, there can be some ‘wobble’ in the way that proteins and DNA interact. Likewise, the regulation of gene activity is not just a matter or on or off. Sometimes the switch flicks to a higher than usual setting, and sometimes it gets stuck on low. Over a large enough number of cells, this wobble averages out so that it (mostly) hardly matters. But when we’re talking about the very early development of an embryo, when tiny clumps of just a few cells are deciding their fate, that wobble can be enough to make a real difference. Like the proverbial butterfly that flaps its wings and causes a hurricane, small changes in just a few cells at just the wrong moment in early development can have a big effect down the track.

  So, we can see that there’s a spectrum of possibilities that encompasses all human disease. There are conditions — like being hit by a car, or suffering the effects of exposure to thalidomide — that are mostly about environment, but are also about genetics — favourable genetic variation, which might protect you from thalidomide, or unfavourable variation, which might make you vulnerable to infection. There are conditions that are mostly caused by changes in a single gene — modified by the effects of other genes a
nd by the environment. And there’s everything else in between, with a great many conditions that are the result of thousands of small genetic nudges interacting with each other, and with the environment.19

  [19 Not a genetic condition, exactly, but eye and skin colour represent something of a special case, with a relatively small number of genetic variants combining to produce most of the variation. There are handy charts available online that explain that blue eyes are a recessive trait, with pictures showing brown-eyed parents having a 1 in 4 chance of having a blue-eyed child. These have the advantages of simplicity and clarity, and the disadvantage of being completely wrong. Eye colour is in fact a complex characteristic, but, unusually, looking at variation in just a few genes — especially HERC2 and OCA2 — can give you a lot of information about eye colour. A group of Dutch investigators, studying a majority blue-eyed population, were able to predict that a person had brown eyes with 93 per cent accuracy using just six variants in six genes. Skin colour has similar genetics, including — unsurprisingly — sharing several of the same genes that influence eye colour.]

  With this understanding comes the possibility that we might be able to use genetic markers to make powerful genetic predictions about health, or about other characteristics. Maybe a single GWAS hit by itself can’t tell you much about your future wellbeing, but what about combinations of hundreds of them? Could you put the information together and make meaning out of it? The answer turns out to be: sort of. So-called ‘polygenic risk scores’ have been put together for various common medical problems: stroke, heart attack, diabetes, various types of cancer, and so on; essentially this is the same as the approach used by Stephen Hsu’s group to try to predict human height. The best of these are starting to become useful medical tools already. For example, a polygenic risk score can be used in combination with other information to calculate a woman’s chance of developing breast cancer, in a way that can potentially change the type of screening she is offered.