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Diabetes MDs Observe Gap between Genomics Knowledge and Personalized Medicine Practice


By Molika Ashford

Discoveries of molecular markers to aid type 2 diabetes diagnosis and personalize treatment are growing, even though the gap between this new knowledge and its clinical implementation remains wide, according to a new report.

Though promising markers are emerging in genomic, proteomic, metabolomic, and epigenetic research, translating these advances into clinical action will require physicians and researchers to focus the wide field of molecular diabetes research, Eddy Karnieli, a researcher at the Rambam Medical Center in Haifa, Israel wrote in his perspective, published in the July issue of Future Medicine’s Personalized Medicine.

Karnieli told PGx Reporter this week that current diagnosis and treatment management for type 2 diabetes has a great deal of room for improvement. The breadth of the field of research into molecular solutions is so wide that little actionable information is trickling down to the frontlines of treatment.

“What we do when we see a diabetic patient is consider the big picture: he is 50 years old with a nice belly coming into the clinic with high glucose. Then … we treat all the patients [with these characteristics] in the same way,” said Karnieli.

Meanwhile, the published literature on the molecular features of diabetes suggests that doctors should not be treating diabetes patients as if they all have the same disease. “We're treating based on the regular paradigms of evidence-based medicine, where you look on the average," Karnieli said. "But actually none of us is an average person."

In his report, Karnieli outlined several key areas where integrating genomic knowledge could lead to more personalized diabetes management and treatment strategies, facilitating early diagnosis, identification of patients at a greater risk of complications, and the development of new targeted treatments.

Karnieli and his co-authors support that addition of genetic and other biomarkers to the traditional diagnostic criteria could improve the pre-symptomatic diagnosis of patients, crucial for reducing or avoiding the sometimes life-threatening consequences of the disease.

In the report, Karnieli et al. cited several studies that have tested whether SNPs and other genetic changes could improve prediction of diabetes risk. Independent of clinical risk factors, variants in TCF7L2, PPARg, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, HNF1B, CDK2NA/B, and HHEX have been found to be associated with increased risk of developing diabetes, the researchers wrote.

However, “the 40 known SNP variants only improved the predictive value for DM2 risk in patients younger than 50 years of age,” the authors wrote, citing a study by a group of Boston hospitals and institutions.

For predicting complications, the group noted the eNOS gene, which was reported to be of clinical relevance to cardiovascular disease and nephropathy in type 2 diabetes in a study by Swedish researchers. But “the mechanism by which such a polymorphism affects the phenotype is as yet unclear, and further studies are needed to confirm these findings,” the researchers reflected.

According to the study authors, associations between variants in the adiponectin gene (ADIPOQ) with circulating adiponectin levels and cardiovascular risk among women with diabetes have also been shown in recent studies.

Genetic variability and presence of polymorphisms, still need further investigation, “particularly when trying to determine the potential mechanisms that could be used as effective tools for both diagnostics and treatment," Karnieli and his co-authors stressed.

Diabetes patients are currently treated with a large portfolio of drugs, spanning nine major therapeutic classes, according to the report. Treatment classes include biguanides, sulfonylureas, thiazolidinediones, meglitinides, a-glucosidase inhibitors, amylin analogues, incretin-mimetics, dipeptidyl peptidase 4 (DPP4) inhibitors, and insulin and its analogues.

Patients are also treated with medication for diabetes-related complications, like statins to treat high lipids or diuretics for hypertension. First-line treatment focuses on lifestyle changes, coupled with the drug metformin, followed by new regimens when blood sugar cannot be maintained.

According to Karnieli, drug response varies widely. “Based on my experience and other people, we give a medication, and some times it doesn't work. It’s a known fact that 50 percent of the medications are actually working and 25 percent are probably causing some side effects, and 25 percent aren't having any effect,” he said.

Because of this, biomarkers associated with treatment response stand to improve safety and effectiveness of drugs in patients who harbor such markers. According to Karnieli’s paper, recent research has investigated the transport mechanism of metformin as a factor in response.

One study evaluated common variations in 40 candidate genes previously associated with type 2 diabetes for their impact on diabetes incidence and their interaction with response to metformin and lifestyle interventions. “The genes encoding the AMPK kinase STK11 and the AMPK subunit genes PRKAA1, PRKAA2 and PRKAB2 were found to be associated with the response to metformin. This promising finding warrants further investigation,” the authors wrote.

Another important point highlighted in the report was that genes don’t paint the whole picture. “If you have mutation of genes, probably you will have some disease. But it doesn't cover all the cases," said Karnieli.

“You also know it from normal practice, if someone is obese and has diabetes, if he loses weight, the diabetes, hypertension, hyperlipidemia can return to be normal,” he said. “For example, all these bariatric surgeries do kind of miracles. The surgeons are doing better for diabetic patients than we, so called experts, do … and it doesn't matter whether you have some genes or not, [since] there are much more pathways involved in this system.”

Karnieli said he thinks advancing research in epigenetics and metabolomics may shed more light. Although there is accumulating knowledge, "it is a very slow process,” he said. “But I think the answer will finally be in combination [of different molecular approaches.]”

At the same time, he said his research underscored how little data sharing there has been among investigators in molecular markers for diabetes. “Every one of us, and I am to be blamed as well, we like what we do, we go deeper in it, and finally we know everything or nothing,” he said.

Because of this, Karnieli said he and colleagues at the Rambam Medical center and Rappaport Faculty of Medicine at the Technion Israel Institute of Technology have decided to hold an international conference in 2012 to try to integrate some of the disparate investigations into one large conversation on moving toward a personalized approach to diabetes. “This is something we are really pushing for,” he said.

Have topics you'd like to see covered in Pharmacogenomics Reporter? Contact the editor at mashford [at] genomeweb [.] com.

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