Wednesday, 16 September 2015

Anatomy of an mainstream science piece

Last week, the Guardian published a Comment by me entitled, ‘Why I'm sceptical about the idea of geneticallyinherited trauma'. In this blog post, I’d like to go through what happened behind the scenes when someone from the mainstream press asked for my views, what my thought process was before I started drafting a response, and why I believe we should all participate more in public discourse on science.

The motivation for the Comment was a short story, published almost a month ago in the Guardian, about a paper that made claims about the transmission of some molecular memory from Holocaust victims to their children via epigenetics. The paper itself was pilloried on Twitter, rightly so in my opinion (one scientist remarked that this is a perfect example of how not to run an epigenetics study). The story was prepared by a reporter covering for Ian Sample (science editor for the Guardian), who was away on holiday; an objective expert opinion was not found for the story, and I think that when Ian returned he felt motivated to redress the balance. Probably because of my active role on Twitter, and with support from other scientists (Matthew Cobb in particular), the door was open for me to pester Ian for a response.

Before you rush to blame the reporter (or journalism, generally) for rushing a story through, it’s important to keep in mind that the media operates under some fairly stringent constraints. First, news must be new, or it isn’t news – so there is always time pressure. In addition, any piece needs to meet two criteria to be broadcast (in print, online, on radio or TV): (1) it must be interesting, and (2) it must be comprehensible to a general audience.


Everyone involved in a large media apparatus (radio, TV, print, etc.), including journalists, editors, subeditors, producers, fact checkers, camera operators and many other professions, aims to maximise interest, accessibility and delivery. For science journalists, “interesting” can mean, broadly, one of three things:

  1. It has, or could have, a direct bearing on the reader/listener/viewer’s life, or in the case of large events, on the lives of a large number of people. Most health pieces and environmental disasters fall into this category.
  2. It is quirky and gives a refreshing perspective on the world, often making use of a cool picture. Big kit falls squarely into this category (robots/satellites sending back the first pictures of a planet / asteroid  / comet automatically max out on this criterion).
  3. It is of global significance and is aligned with burning issues in mainstream politics, for example climate change or epidemics. If this category is mined heavily by many outlets at once (i.e. fuels the bandwagon), then at a certain point everyone has to run some part of the story to avoid alienating their audience.
The best popular science stories weave in elements of at least two categories: e.g. local flooding and epidemics, or a striking image of nature/human anatomy with a healthcare angle. Making a story appealing and digestible is a big part of the science editor’s craft (more on this below), and a priority for the readers/viewers, etc.

Is ‘right’ interesting?

Whether the science is ‘right’ or not doesn't always have a lot to do with whether it is interesting. This aspect of a story is usually the domain of the science journalist and/or editor, whose personal credibility is on the line (and who must avoid landing in legal hot water; though for the purposes of legality, checking the “peer reviewed article” box seems usually to be enough). Science stories can easily be ‘interesting’ but not ‘right’ – and science editors get bombarded with press releases focused far more on the interesting. 

Thankfully, the science editors I know do care a good deal about the correctness of the pieces they put in – but that doesn’t help them find interesting stories that will capture their audience’s attention. And because covering ‘science’ means fielding everything between astrophysics and zoology, it is a lot to expect that everyone involved will have enough of a working knowledge of the science and communities involved to present a balanced view of any subject.

Pitch in.

So, in short, reporting on science is a hard job – though it is also fun to be able to write about science all the time. If you are ever contacted by a science editor to give your opinion, please, please respond! And think carefully about the overall message. If the science is sound, it won’t hurt to allow the ‘interestingness’ to come through. If you do not think the science is sound, say so, outright and clearly (the journalist can canvass others for opinions; be frank, but not harsh).

What’s the angle?

So when I was asked to write the Comment for the Guardian (triggered by that epigenetics piece), here is what went through my head:

  1. I’ll need to explain the hideously complex, overlapping definitions of ‘epigenetics’, and give some insight into the disputes around this. Could easily use as examples the excellent pieces by Mark Patshne, or the (very British) ‘broad church’ compromise definitions by Adrian Bird, and touch on the almost 50 years of debate around this word. Caveat: Good to humanise science, but is this too ‘inside baseball’ (to use an Americanism)? However interesting this is to scientists, it doesn’t score well on any interestingness criteria for the general audience.
  2. I could delight in the sheer inventiveness of biology around epigenetics processes… X chromosome inactivation in females, for example: tortoise-shell (or calico in the US) cats, women with multi-coloured irises. Lots of potential for visuals with those. Or the Calipyge mutation (‘beautiful buttocks’) in sheep: a serious use of differential imprinting, and you get to use the phrase ‘beautiful buttocks’ – a sure win! Plus, pictures of proud farmers looking at their prize lambs... For additional interest, could also write about the long-standing discovery/exploration of epigenetics in flowering time in plants. Absolutely satisfies category 2 criteria: a quirky look at the world, with good visuals.
  3. Is this a good example of the limits of using peer review as the sole measure of quality/correctness? This is a really important issue, but this paper is by no means the first or last case of things going wrong. But, realistically, this is almost certainly uninteresting to most readers. More a matter for scientists to explore amongst themselves in specialised press, or for a science journalism forum.
  4. Use this as an opportunity to explore general misunderstandings of genetics (and, in part, epigenetics)? The theme of genetic determinism is currently too strong in mainstream media, and this needs counter balancing.
Clearly, I went for 4 – but 2 would have been an easy choice (indeed, I think that article should be written sometime!). The other options would never make the cut.

Can I go beyond just explaining this (bad) piece of science?

For a long time I have been watching our culture embrace genetic determinism, more and more. In addition to the commonplace usage of ‘DNA’ as a metaphor for ‘core values’ (see my previous blog post about this, and Private Eye’s satirical weekly column, ‘DNA’), I’ve had conversations with non-scientists about the predictive power of DNA that bring up such concerns as, “I wouldn’t want to know my genome because I don’t want to know the time of my death”. The person I was speaking with in that case was quite convinced that the end point of all these genetic discoveries was a sort of complete roadmap of a ‘healthy’ life, and certainty about which diseases one would get and when. For him, personally, it was simply better ‘not to know’.

In contrast, there is no shortage of opportunities for science journalists to investigate claims made about beauty creams and health schemes ‘tailored’ to a person’s individual genetics. 

The genetics of skin and of exercise response are indeed interesting, but it is hard to establish (to say the least) any clear-cut genotype-specific environment effect. Many of the people marketing these schemes are playing on the ‘DNA is the real you’ meme as if it is a given, rather than checking whether there is any actual scientific basis for that assumption.

The drafting process

As with all my public pieces, the article was a collaboration with both Mary Todd Bergman, who I bounce ideas off and she also edits much of my work (including this blog piece). For the Guardian piece, Ian Sample also went through several iterations with me to improve readability. This process is invaluable – it is so hard as a practicing scientist to read your words back as 'lay person', and to stick with using everyday words rather than using specialised (and thus precise, but inaccessible) terms.

I also had to plot a careful course around the word “epigenetics”. It is a very frustrating topic with at least three 'mainstream' meanings, and numerous attempts to define it. After I had a reasonable draft I sent it around a broader group of people (I will mention many of them below) but in particular to Anne Ferguson-Smith, who I consider one of the best scientists studying epigenetics. She helped change the tone of the piece, in particular stressing the importance and soundness of developmental and environmental changes in the epigenome (contrasting that to trans-generational epigenetics).

Going through multiple drafts greatly improves accessibility (the soul-mate of interestingness) – what you write is not necessarily what people read. Of course, some things are lost in the smoothing process. For example, explaining imprinting didn’t make the cut. Getting across certain ideas was very tricky, for example the fact that in genetics we’re classifying the proportion of variance in some populations, but often deliberately sampling where we fix many other features (I hope the thought experiment of setting the same exam to a mixture of French and English people is a good one).

The broader group?

In science, nobody works alone – just as in writing this piece. But news pieces are written back-to-front, with the conclusion right up top – so things like references, citations and background tend to get squeezed out. (Anyone who writes a lot of science papers will know how weird it can feel not to include a list of references.) It doesn’t feel right to see just my own name at the top of that Guardian piece. Really there are four contributors to this article: myself, Ian, Mary and Anne. Furthermore, the ideas I express here are the result of decades of discussion with people. Science is always a ‘team sport’ and even in a paper you can seldom provide a reference for all the things you’d like to.

I’ve been discussing the ‘over-reach’ of the public’s general grasp of DNA for a while, and as with all really interesting questions my views have been heavily influenced by many of my colleagues. In particular discussions with both George Davey-Smith and John Danesh have really helped me understand the epidemiologist’s view of this. George and John live and breathe human variation every day of the week. Long-standing epigenetics experts like Anne Ferguson-Smith, Stephan Beck, Eileen Furlong and Ian Dunham, and the people I met in ENCODE, including Brad Bernstein, Peggy Farnham and John Stamatopolous, were great teachers in the complex world of histone modifications and (somatic) epigenetic components. Clinician-Scientists such as Nazneen Rahman, Helen Firth and Stuart Cook have opened my eyes to the complexity of ‘well established’ genetic variants, and discussions with people in the broader quantitative genetics community, including Peter Visscher, Trudy Mackay, Jonathan Flint and Chris Haley, and on the Genome Campus Oliver Stegle, Nicole Soranzo, Jeff Barrett, Carl Anderson and Matt Hurles have educated me about the details of these models and the real-life world of complex trait genetics. (I still often only have an intuitive understanding of some of the maths, which gets amazingly tricky – like when you are diagonalising matrices inside equations with Kroneker product schemes, and dealing with non-negative aspects of the matrices, and fixing it all up…).

Discussions with people in all these very different fields have helped shape my position about the way we have communicated with the wider world about genetics and genomics.

DNA is not your destiny, and we need to say it loud

I hope the piece in the Guardian contributes positively to the public discourse around genetics. We are going to be making more and more detailed discoveries about human traits – diseases, yes, but also everyday traits such as human height, normal organ processes, mechanisms that drive behaviours like risk taking, exam achievement, spelling ability, musicality, criminality… Each of these is a totally sensible thing to study. But interpreting the results, both scientifically (read the Methods carefully!) and, more importantly, in a social sense, is going to be difficult and demand a huge time investment.

As practicing scientists, we need to continue laying the groundwork started long ago by many others (see Matt Ridley’s Nature via Nurture, 2003), engaging consistently and non-judgmentally with our communities and policymakers about out work. There is a real task ahead of us in providing an accessible way for people to digest this information. We should take every opportunity to communicate on every level, from the most basic to state of the art. Only then can society really use the hard-earned information gleaned from genetics appropriately, and for the greater good.

Thursday, 7 May 2015

Human as a model organism

Model organisms have provided the foundation for building our understanding of life, including human disease. Homo sapiens has joined this select group, adding knowledge we can apply to our myriad companion species. But to resolve even one small part of the moving, shifting puzzle of life, we need them all.

Biology is incredibly complex. Even the simplest bacteria make intricate decisions and balance different demands, all via chemical reactions happening simultaneously in what seems like just a bag of molecules, called a cell. Larger organisms all start as a single cell and eventually become living creatures that can fly, or slither, or think – sometimes living for just a day and sometimes for centuries.

Whatever the process, whatever the outcome, it all begins with information, recorded in a tiny set of molecules (DNA) in the very first cell. How that information made it this far, and how it is now composed, comes down to the twin processes of random change (mutations) and competition between individuals, giving rise to evolution. Evolution has, quite amazingly, given rise to everything from uranium-feeding bacteria to massive sequoias and tax-filing, road-building, finger-painting humans.

Modelling life

Unpicking this complexity is hard, in part because so many things are happening all at once. We’ve been working on it for centuries, building layer upon layer of knowledge collectively, in many labs throughout the world, usually relying on specific organisms where we accumulate large amounts of knowledge on the processes of life. These ‘model’ organisms, for example the gut bacteria E. coli, are selected for their ease husbandry and other features of their biology. Interestingly, most of them have been our companions or domesticated in some way throughout our explosive growth as a species.

To create models of animal life processes at the simplest level, we use organisms like European and African yeast (used for both baking bread and making beer), which has a nucleus (like all animals, they are eukaryotes). We use the humble slime mould, which spends most of its time as a single cell but, in extremis, will band together to form a proto-organism that has given us insights into signalling. Taking it up a notch, we are helped by pests that have lived off our rubbish since our earliest days in Africa: fruit flies, mice and rats provide profound insights into animal life. Even the model worm C. elegans, which helps us understand development, could be considered ‘semi-domesticated’ (though no one really knows where ‘wild’ C. elegans might live).

Each of these models has its strengths and weaknesses: the time it takes to breed generations, the effort involved in handling them, the availability of automated phenotyping systems, the flexibility (or lack thereof) of their cellular lineage, and more exotic features, such as balancer chromosomes, RNAi ingestion, chromosomal engineering. But they all share one distinct quality: they are not human.

Using ourselves?

Using Homo sapiens as a model species to understand biology has many advantages, and some important drawbacks. Leaving aside for a moment the interaction with research into human disease, what are the benefits of using ourselves as an organism on which to model basic, fundamental life processes?

·            Humans are large, so we can acquire substantial amounts of material from consented individuals either from living persons (e.g. blood) or via autopsy;

·            The extremely large population can be accessed relatively easily, with no on-going husbandry costs;

·            Wild observational studies (i.e. epidemiology) are feasible to deploy at scale, though at considerable cost;

·            The population has good genetic properties: it is outbred, and mating is fairly random with respect to genotypes, usually with only geographic stratification;

·            Many phenotyping systems are designed explicitly for this organism, in some cases with a high level of automation;

·            An on-going, proactive screening process for rare, interesting events (i.e. ‘human clinical genetics’) are available in many parts of this population at the scale of millions of screening events each year;

·            Cells from this organism can be cultured routinely using iPSC techniques, and these cellular systems can be genetically modified and made into functional tissue-scale organoids;

·            Limited intervention studies are feasible (if expensive);

·            Research on this organism is well funded, thanks to widespread interest in human disease.

The drawbacks:

·            There are no inbred lines for Homo sapiens;

·            The large size and tissue complexity of this species, in particular the brain, presents significant challenges to understanding cellular and tissue behaviour;

·            The organism cannot be kept in a strictly defined environment (though an increasing number of aspects can be monitored in observational studies);

·            Explicit genetic crosses cannot be done (though the large number of individuals make it possible to observe many genetic scenarios in the population);

·            Genetically modified cells cannot be used to make an entire organism;

·            Intervention studies are quite limited by both safety and expense;

·            Ethical issues, which are important when studying any species, are more involved for Human – even for basic research.

An old story

Using Homo sapiens as a model species is not a new idea – it has been around since the dawn of genetics and molecular biology. Studies of human height motivated the early theory around quantitative genetics. Quite a bit of mammalian (and general eukaryotic) biochemistry and genetics was originally uncovered by discoveries of inborn errors in human metabolism in the 1960s and 1970s, and was confirmed by biochemistry studies in cow and pigeon tissue. And robust cancer-derived cell lines – most famously HeLa cells – have been used in molecular biology for decades.

But the downsides to using humans as a model species are far fewer in number now than they were two decades ago, when the human genome was considered to be so large that a major, global consortium was required to generate it. But the human genome is dwarfed in size and complexity by bread wheat and pine, whose genomes are being untangled today. The cost of human genetics studies has plummeted so that large populations are more accessible and easily leveraged (a genotyping array now costs under €50 and sequencing under €1,000), which is a major benefit for doing statistically robust studies. The result has been a resurgence of common and rare genetic approaches. The drop in sequencing cost has allowed more scalable assays, such as RNA-seq and ChIP-seq, which let us work routinely on the scale of a whole human genome.

A decade ago there was a far wider gap between experiments that were feasible on Drosophila, C. elegans or the yeasts, but not on human beings. The landscape has changed.

Human disease

The global economy is a human concept (though it affects all species) and a big chunk of it (10% to 17% in industrialised economies) is spent on healthcare. That is a huge amount of money. A considerable amount is already spent on clinical research, but the advent of inexpensive techniques to measure DNA, RNA, proteins and metabolites presents massive, new opportunities. It is now possible to blend scientific approaches that have traditionally been separate – experimental medicine and genomics, or epidemiology and bioinformatics – to exploit these measurement techniques alongside traditional clinical approaches.

The primary motivation for all this activity and expense is to understand and control human disease. But health and disease are constantly in flux, in humans as in all species, and often the process of understanding human disease is really just the same as understanding human biology – and that’s not so different from understanding biology as a whole. Fitting all the pieces together requires taking the best from all fields, and that is in itself a huge challenge.

Traditional models, rebooted

There is justifiable excitement around new opportunities to study humans as a model organism, but it is simply not the case that the established model organisms will become less and less relevant. Placing too strong an emphasis on Human studies could lead to inadvertently hindering research on other organisms, which would be counterproductive.

‘Model’ organisms help us create ‘models’ of life processes – they do not serve as ‘models’ for human organisms. Our grasp of molecular biology is still quite basic indeed: we have a firm grasp on only just over a third of protein coding genes in humans, and this number is not much higher in simple, well-studied organisms such as yeast. Even in cases where we have ‘established the function’ of a set of genes and can tie them to a specific process, we still have huge gaps in our comprehension of how these particular molecules can create exquisitely balanced, precise processes.

Leveraging the unique properties of different model organisms provides opportunities to innovate. For example, one remarkable paper demonstrates how a worm ‘thinks’ in real time, monitoring the individual firing of each (specifically known) neuron in the animal as different cues are past over its nose. The growing set of known enhancers in Drosophila allows for the genetic ablation of many cells, and the incredible precision of mouse genetic engineering allows precise triggering of defined molecular components. None of these experiments would be even remotely feasible in Human.
We would be very foolish to take a laser-like focus on this rather eccentric bipedal primate, however obsessed might be with keeping it healthy, happy and long-lived.

Our understanding of development in organisms, of homeostasis within organs, tissues and cells, and of the intricacies of behaviour is only just starting to develop. Metaphorically speaking, we have lit a match in a vast, dark hall – the task of illuminating the processes that drive these molecules to create full systems (that go on to type blog posts) is daunting, to say the least.

Hedging our bets

There are many hard miles of molecular and cellular biology ahead to improve our understanding of biology, with leads to follow in many different models (including human!) using many different approaches. This deeper understanding of biology will directly impact our understanding of human disease in the future. We need to spread our bets across this space.

Clinical researchers might have a harder time managing this, as the necessary focus on Human to understand human disease makes it all to easy to dismiss the future impact of other organisms on understanding human biology. The majority of molecular knowledge they currently deploy in their research is built on studies of a very diverse set of organisms. Useful and surprising insights and technologies can be gleaned from any organism.

Basic researchers, on the other hand, might dismiss the advent of human biology because it places inappropriate emphasis on applied research into the specifics of human disease. All human studies are not necessarily translational, and in any case the interweaving between understanding biology and understanding disease makes it impossible to really separate these two concerns.

To Human and back again

Over the next decade, the integration of molecular measurements with healthcare will deepen. This will almost certainly have a beneficial impact on the lives and health of many people worldwide. It also provides huge opportunities for the research community – obviously for applied research but also for curiosity-driven enquiry, as this massive part of our economies will generate and manage information on ourselves.

We should exploit this to its fullest so that we can understand life, on every scale, in every part of the world we inhabit.