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Looking to the Future, Heidelberg MD Sees Nothing But Haplotype


At A Glance

Name: Bernhard Winkelmann, director of the unit of pharmacogenomics/applied genomics, University of Heidelberg; associate professor, cardiovascular medicine

Age: 47

Background: MD, internal medicine from University of Mainz; residency at Frankfurt University

Most genotyping experts won’t admit it in public, but there is a friendly feud simmering between proponents of SNPs and proponents of haplotypes. Though both disciplines rely on similar technologies, and the results of their studies aim at similar goals, in the end they are competing for a shrinking pot of cash and clout.

For Bernhard Winkelmann, of cooperation unit of pharmacogenomics/applied genomics, University of Heidelberg, there is no doubt which discipline is worthy of his allegiance. He is working with researchers in Great Britain to uncover haplotypes implicated in cardiovascular disease, and has also begun looking into ways in which gene-expression data and proteomics tools may nurture his project. “It’s slow going,” he said. “Genotyping is so advanced compared with proteomics, that you get all of this data, and when you try to bring in the proteomics component you wind up waiting!”

SNPtech Reporter spoke with Winkelmann this week.

What are your thoughts on the role of haplotyping in drug discovery?

For me, I am inclined to be positive. I must admit the scientific evidence that is out there is not so overwhelming. But that does not mean that it will not happen in the near future. Haplotypes are just ordered arrays of SNPs, and this is just more information and better information. It is a better characterization of the individual.

Haplotypes more or less attach some evolutionary information to a subject. That means that if I group individuals based on haplotypes, I more or less group them by their genealogical history — that is, some might have originated from, say, Italy, while others may have originated from Iceland. Especially in the US, you can group people that belong together, which means they might behave similarly [in response] to a medication.

Doing this by SNPs is not bad if you have a very powerful SNP, but generally this is not the case. And I can find 10 or so publications that will find that the haplotype is always better than the single genetic variant.

Do you think haplotypes eventually will usurp SNPs as drug-discovery clues?

Yes. It is not so much different; instead of genotyping one SNP you use three to five, probably not more. There may be a little more effort, but the haplotype itself is generated mathematically anyway. You still use more or less the same genotyping technologies but you use computers to characterize risk scores.

Do you think haplotyping is the poor relation of pharmacogenomics? Does it have the same clout within the drug-discovery industry as SNP-genotyping?

The problem is that, for me as well as for other researchers, the concept of a genetic variant and a SNP is just easier to grasp.

Usually why [haplotyping studies are] not done is also a matter of resources — you need more money and more time to do it — and a lot of people were not aware of how to calculate the haplotypes, but now there are so many software products out there it’s not a big deal anymore.

However, I see [haplotype studies] happening more often, and you’ll begin to see more and more papers appearing in one or two years from the major research groups, which are already focusing more on haplotypes.

Tell me about the haplotyping research being conducted at your lab.

At the moment … I’m collaborating with the Sanger Center. They are conducting a resequencing project of the entire human genome, and they have selected a set of genes. Right now, we are defining platelet genes. First if all, to define what is a platelet gene, we conduct gene-expression studies in humans to find out which genes are expressed in platelets.

When you find them — we found there are there are 3,000 of them — you take these genes, sequence the genomes of 15 individuals to find all of the SNPs in those genes, and define haplotypes. And those haplotypes will be used as markers to test large cardiovascular cohorts.

We have a big ingoing program that will start by the end of the year to test these results in large clinical cohorts — about 20,000 patients or so.

Who is paying for this?

At the moment this research is funded by our own resources [Sanger and Heidelberg]. But we hope eventually to find funding from the European Union, and of course with pharmaceutical companies. At the moment we are in the happy position where everybody has money of their own to carry this out.

But eventually you want to get pharmaceutical investment?

Yes. There’s already a lot of interest among pharmaceutical companies, and I can tell you that big pharma companies would have paid the full amount [of the research]. But we said, ‘No, this is public-domain knowledge, and we don’t want it to get proprietary right away.’ The data that the Sanger Center generates, it puts into the public domain. …

We hope to identify hap markers that are very important for sudden death and myocardial infarction, and can trigger new drug discovery.

Where do you see your haplotyping research in one year? In five years?

In one year we will have started doing the patient cohorts, and in two years we’ll have learned which are the markers. We’ll find out what the genes and platelets are doing. And this could spur a whole new knowledge of platelet physiology, because at the moment a lot is unknown about half of those genes. This means that we could get potentially fascinating new therapies in five years.

What our aim is — and this is new; we’ve never talked about this — is to get the patient involved. We want to enable each individual to have access his own genetic data: He will have his code, and he can access it. Or he cannot — maybe he knows an expert. We feel that if you give something to someone then you should still be able to get access to it.

At the moment genetic research says that, ‘OK, we’ll take your DNA, but we won’t give you the results because we still don’t understand it.’ But even if we don’t understand it we feel the patient still has the right to have the information to his sequence data.

Isn’t that ethically charged? If someone has access to her complete sequence, what if that person learns that she carries a mutation for a disease that is incurable or untreatable?

Yes, but I feel that there first should be some adequate training. Plus, from the aspect of cardiovascular disease, these diseases are all complex genetic diseases. There is not the single mutation. I feel it is extremely wrong and not very nice of those biotech companies who release those testing for hypertension and stuff like that.

This is totally ridiculous, but some people feel that if they do a test, and if it is positive or negative that it means something.

And this is not the case at the moment. It is just not possible that genetic testing can predict a response to a medication at the moment. The problems of genetic factors plus environmental factors means that we do not know enough to say for sure how someone will respond to a drug.

How has your research expanded?

I also perform studies in gene expression and proteomics. For example, I would give a drug to a patient in order to find out what the differences in gene-expression patterns are, and what the differences in proteomics are. And then I want to match those two, and eventually, once I have those data, I go back to the genotypes and to the haplotypes and I compare all of these data sets.

Also, I want to go more into bioinformatics. I already interact with some of these companies in the market — like Molecular Mining and Lion. We have an ongoing research collaboration with Molecular mining.

I feel that there is a trick to mine the data efficiently, and one needs a special knowledge. Once you do this, though, you will be able to detect patterns within proteomics, from gene expression, which you link back to haplotypes, and define two or three haplotypes, and in the process get a handle on a really complex disease. You may also find out which person is at risk for developing a certain disease — in our case cardiovascular disease — and you can predict how this person may respond to a certain drug.

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