Many diseases are multifactorial, many diseases are complicated interactions between the genome and the environment. But this in no way diminishes the importance of genomics and proteomics. It in no way invalidates the work I do on fruit flies, or the work that the lab upstairs does in sequencing the human, mouse, rat, and Dictyostelium genomes (among others). To say otherwise is to misunderstand the potential of genomics.
One on level, you are correct. It takes complicated computations to determine linkage analyses, LOD scores, and the like which are only correlated with often rare forms of the disease. We have little way of scientifically assessing the impact of environment on disease, and identifying environmental stimuli that participate in even the most common diseases. For instance, multiple sclerosis is more common in people who spend up until age 14 in the north. We have no idea why. We can only separate phenotypes that stand 3 standard deviations apart. Etc. etc.
We obviously need more powerful techniques to identify culprits. The field of genetics is embracing computer science, supercomputing, and advanced statistics. We have people pursuing PhDs in computer science and full-fledged computer scientists in our department. We now employ many statisticians, and have a few as primary faculty. We are also developing new techniques, like gene chips, to assess changes not one gene by one gene, but hundreds or thousands of genes at a time. We are already starting to make some headway into the quagmire.
On another level, your irreducible complexity type argument is false. We start with a small lead, any lead, in humans. We move into model organisms, from bacteria through yeast, then worms and flies, and mice. The amount of work that can be done quickly, the amount of data that can be generated, and the amount of insight that can be gained is incredible. Given a good model, even complicated interregulatory networks can be dissected. I work on patterning in Drosophila, a process closely mirrored and somewhat clinically applicable all the way through humans. It is a dense network of interregulatory genes, and much of it applies all the way through higher eukaryotes.
This process is greatly facilitated by genomics. Let’s say we isolate a gene, let’s call it hABC, in a rare form of familial Alzheimer Disease. At this point we know nothing about hABC. We find a fly homolog dABC. We perform coimmunoprecipitations, binding assays, yeast two-hybrids, and modifier screens to identify binding partners and interactors of dABC in the fly – genes involved in the same or similar pathways. We use cell culture and straight biochem to identify novel function of the gene product. We use genomics to move into the mouse, identify mABC and its partners, and knock out the homologs. Lo and behold, we get a similar phenotype – let’s hope for neuronal degeneration. We then move into humans using genomics and can work through a set of candidate genes identified as potential partners of hABC. We can then start to pin more forms of Alzheimer Disease on polymorphisms and mutations in these genes. At very minimum, we end up with a detailed knowledge of how hABC is leading to Alzheimer Disease, and of how the pathology of Alzheimer Disease unfolds.
How does this apply to disease, you ask? Well, easy. The new strategy of drug design is to seek out and inhibit specific protein targets. This leads to drugs with maximal action and minimal side effects – look at the new set of AIDS drugs, which are specific HIV protease inhibitors. Protein targets are quickly identified by these methods, of which genomics is a crucial tool. If we can identify function of some of these targets (again by genomics) – let’s say one is a serine/threonine kinase – we can try out a set of kinase inhibitors to see if we can specifically inhibit one of our targets.
Lastly, there is always science for science’s sake. We didn’t go to the moon to cure disease. We didn’t sequence the genome (entirely) to cure disease. It is an incredibly useful repository of information, made free to all seekers, which eventually will serve to catalog what makes each of us human and what makes each of us different.
In the future, we hope to be able to directly and permanently modify the genome or gene transcription, by something like gene therapy or a related technique. We are not there yet. But the groundwork we are laying now will be invaluable if and when these techniques come on line. All of these things combine to give genetics and genomics a potential far too great to be ignored.
