A physiogenomic study of patients on two antipsychotics – Eli Lilly’s Zyprexa and Janssen’s Risperdal – found potential DNA markers that can predict the likelihood of patients developing pre-diabetic side effects such as weight gain.
The study, entitled “Physiogenomic comparison of weight profiles of olanzapine- and risperidone-treated patients,” was published in the Jan. 2 issue of Molecular Psychiatry, and was partially funded by Genomas and a small business innovation grant from the National Institute of Mental Health.
The study used Genomas’ PhysioGenomics technology, a biomedical platform that compares DNA variations in a patient group to physiological characteristics or reactions. The PhysioGenomics platform is currently under development, and will be on the market in late 2008. Genomas said it plans to seek FDA clearance for the product.
Genomas CEO Gualberto Ruano told Pharmacogenomics Reporter this week that the study results will have a “considerable and quite profound” impact on patient care.
“In the future, rather than prescribe this antipsychotic medicine or the other, you will have a prediction of which one of these medications will have the least risk of developing weight in a specific patient,” Ruano said. “Doctors will utilize that information to prescribe the drug and protect the patient from developing the side effects but at the same time allow the patient to benefit from the medication.”
The study involved Genomas, the Institute of Living at Hartford Hospital, and the University of Kentucky Mental Health Research Center at Eastern State Hospital. It followed 67 patients on olanzapine, also known as Zyprexa, and 101 taking risperidone, or Risperdal, all of whom were part of ongoing genotyping studies at the Institute of Living in Hartford and at three Kentucky state hospitals.
A total of 29 SNPs were selected from 13 candidate genes that were indicators of pre-diabetic conditions such as peripheral lipid homeostasis or central appetite regulation.
Genomas’ PhysioGenomics platform analyzed the distribution of patients’ responses and determined how the frequency of the SNPs varied among individuals with similar responses to a drug.
“When configured into SNP ensembles with interpretative algorithms, the company’s product … enables clinicians to perform DNA-guided drug selection considering an individual’s innate likelihood of developing side effects,” Genomas explained in a statement.
“By doing that analysis in various genes related to cholesterol metabolism and appetite, we were able discover that these drugs, though they are in the same class — atypical antipsychotics — have different genetic patterns,” Ruano said. “Olanzapine has a high correlation to genes related to cholesterol metabolism. In contrast, risperidone has relationships and associations to genes that control appetite.”
The investigators assessed the physiological-genomic associations with
weight profiles of patients in both drugs. Covariates such as age, gender, race, and study site were also accounted for.
“The data show that physiogenomic associations of patient weight profiles can be established for genes in the pathways encompassing appetite peptides and peripheral lipid homoeostasis, thereby differentiating olanzapine and risperidone side-effect profiles,” the study authors concluded.
Specifically, the researchers found that “a certain series of SNPs in cholesterol metabolism-related genes coding for apolipoproteins E and A4 were significantly associated with the weight profile in the olanzapine-treated group but not in the risperidone group.”
For appetite-related genes, the leptin receptor in the neuropeptide Y receptor Y5 was significantly associated with the weight profile of the risperidone-treated group, but not with that of the olanzapine counterpart.
Additionally, gender was a significant factor in the risperidone-treated group, with men experiencing more weight gain than women.
This year, Genomas plans to follow up this research with clinical validation studies for olanzapine and risperidone, as well as extend the physiogenomic research to other atypical antipsychotics out on the market.
A Different Kind of Dx Company
Ruano noted that all of Genomas’ technology programs are partnered with hospitals to ensure that the company’s platforms are “embedded in the health-care delivery system.”
Diagnostics companies have complained that physicians have been reluctant to use genetic tests in their practice. An FDA official recently noted that labeling updates recommending the use of genetic tests have done little to change physician behavior in this regard [see PGx Reporter 01-03-07].
“Our strategy has been to never impose the technology on physicians, rather demonstrate the benefit to the patient. Once you do that I think it will become very clear that this is a way to prescribe these very effective medications [that] have potential side effects,” Ruano said.
“Our strategy has been to never impose the technology on physicians, rather demonstrate the benefit to the patient. Once you do that I think it will become very clear that this is a way to prescribe these very effective medications [that] have potential side effects.”
Ruano highlighted Genomas’ partnerships with mental health hospitals for this particular study with atypical antipsychotics to note that physicians will be more attuned to using the PhysioGenomics platform before prescribing the drugs.
“Rather than impose technology on people, we just say, ‘This is what we do to help your management,’” Ruano said. “That makes us very different from other companies that are just pure diagnostics developers. We consider ourselves a health care-management company with DNA-guided support.”
“This allows us to understand the particular needs of physicians so we can address them,” he said.
An estimated 14 million patients suffering from mental health diseases such as schizophrenia, bipolar disorder, obsessive-compulsive disorder, and generalized anxiety disorder use atypical antipsychotic drugs. However, these drugs can cause diabetic symptoms, such as weight gain, in approximately one-third of patients who use them.
Additionally, the effect profiles of different antipsychotic therapies vary, so drugs within the atypical antipsychotic class may have distinct side effects that are different from others in the class.
“You have to think about the stakes at hand,” Ruano said. “If you have a very young person in their 20s with mental disease, and you prescribe them these medications, then you are going to treat the patient for one thing and you are going to induce a different kind of disease that they didn’t previously have.”
“So the stakes are very different when you talk about side effects as opposed to just efficacy.”
Although the PhysioGenomics technology is not yet on the market, Ruano rallied for the diagnostic noting that treating side effects resulting from olanzapine and risperidone can amount to significant health care costs.
“If you look at the studies that have been done on antipsychotic drugs, most patients stop taking the drugs in less than one year because of the side effects,” Ruano explained. “By making patients take the medication on the [PhysioGenomics] system and avoiding the medical complications of the side effects [that] have to be treated, we believe the diagnostic system more than pays for itself.”