Telling someone that she has the gene for Parkinson’s or the gene for restless leg syndrome is a bit like telling her that her house has termites or sits on a toxic dump. It implies that her misfortune is that she has something that most people don’t have, and further that all would be well if only she could get rid of the termites or toxins.
Genes are not like that, though. They are not things that some people have, and others do not. Approximately 23,000 genes are in the human genome, and all of us have pretty much the same number, give or take a few dozen. What we actually have are different flavors of genes. The technical term for a gene flavor is allele, pronounced ah-lee-el: Whenever you read the word “allele,” think of chocolate and vanilla ice cream. Alleles are different versions of the same gene, just with different spelling and slightly different function.
In fact, in many cases, when a gene is associated with a disease it is because the gene is in some way broken or missing. Just getting rid of the gene would not help. A better house analogy than termites and toxins might be damp foundations, or cheap window frames. The house is basically the same as everyone else’s, but problems arise because it just wasn’t built as well as it should have been. Generally in such cases, many other things also are likely to go wrong and in this sense, too, the analogy with complex disease is improved.
Similarly, it seems that almost daily we read proclamations that scientists have discovered the gene for stroke or the gene for homosexuality. In almost every case, what they really mean is that the scientists have discovered a particular variant of a gene that slightly increases the likelihood that some people will suffer strokes or prefer their own sex. Sometimes the headlines replace “the” with “a,” which is definitely better but still conveys the impression that the purpose of such genes is to cause the disease or trait. Actually, the genes universally promote what we colloquially refer to as normality. They come in different alleles, and under some conditions particular alleles promote disease, or conditions we choose to label abnormal.
Contemporary genetic research is focused on finding these alleles and is as much about basic understanding of what they do as it is about finding cures for specific diseases. This is because there is little prospect of finding new cures for cancer until we understand why tumor cells grow out of control in the first place, and the next drugs for treatment of depression won’t arrive until we appreciate what is wrong deep inside the brains of the chronically sad. This makes sense if you consider that most of us would prefer that our automobile mechanic understand how the engine works, rather than just try the same old fixes he’s always used in the past.
The advantage that a mechanic has is that humans made cars, so we know not just what every part does but also what its purpose is and how it interacts with all the other parts. Biomedical researchers now have a pretty complete parts list and a fair idea of where each part goes, but there is still much to be learned before we know what all the parts do and how they fit together to make a healthy person.
Much genetic research involves pulling apart and putting back together model organisms that we can manipulate, like mice and rats and zebrafish, and even flies and nematodes. Increasingly the tools are at hand to do it with humans directly—at least, the pulling apart bit. Also, for just about every gene, somewhere in the world there is a person with an allele that does not work, and many thousands of these are responsible for rare syndromes. They are teaching us a lot about how things function, but for the most part don’t explain the common diseases that afflict us all.
To this end, a parallel mode of genetic analysis is much less familiar to most people and yet influences all of our lives on a daily basis to a much greater extent than the genetics that we learn in school. Variously referred to as quantitative genetics, or by phrases such as complex disease, multifactorial trait, or polygenic disorder, it is the study of how common variants in many genes interact with one another and with the environment to produce the biological variation that surrounds us. Genes are fundamentally interactive entities, working together, adjusting to the environment around them, molding organisms but not determining their destiny. For anything the least bit complicated, it truly takes a genome.
Most of the differences between species are of this type, as are the attributes that make us unique, from body shape and facial features to metabolism and even aspects of temperament. So too are the diseases that touch every one of us directly or indirectly as they afflict friends and family: cancer, diabetes, cardiovascular disease, asthma, and depression. The language associated with quantitative genetics switches from the imagery of control, determination, and causation, terms popularly associated with genetics, to the less strident tones of susceptibility, influence, and contribution. This book is predominately about the genetics of complexity.
Perhaps another analogy might make the distinction clearer. All of us are probably painfully aware of the impact that one individual can have on a business. If the CEO, or CFO, or CSO, or Director of IT, or head housekeeper for that matter, stops working or starts making bad decisions, the company can deteriorate rapidly. Yet it is the more subtle failings or distractions of multiple employees that most often disturb the health of the company even in good times. Two co-workers are going through a divorce, a supervisor is having an affair, the junior VP for marketing is caring for her ailing mother, and one of the bookkeepers has repetitive strain injury. Nothing is particularly unusual about any of these circumstances, and each of them is almost to be expected in even a moderate-sized group of people. For the most part organizations can and do deal with them, but mix them together in certain combinations and pretty soon potential dissipates, opportunities are lost, maybe employees start leaving, and things can fall apart. Such is also the fate of our genomes: Genes are ultimately individuals that have to work together, but they’re not perfect, and sometimes the pieces just don’t mesh.
Far from being selfish robots, genes are in fact little molecular existentialists. Contemporary molecular biology is about relationships and networks. It is the context within which a gene is used that defines what it does and what it is. Sure, certain genes are essential for the development of the eye or the heart, but these same genes do other things in different contexts. Think not of genes as dictators, but rather as a parliament of constituents—a parliament that on the whole does a pretty decent job, but sometimes messes up, with dire consequences for the health of the organism.