Skip to main content
Premium Trial:

Request an Annual Quote

International Study Hopes to Identify Genetic Markers to Predict Response to Antidepressants


A group of research centers spanning five continents is in the middle of a clinical trial intended to identify genetic and other markers that can predict response to three antidepressants.

According to Subhdeep Virk, a psychiatrist and principal investigator of the study at Ohio State’s Wexner Medical Center, the International Study to Predict Optimized Treatment of Depression, or iSPOT-D, is the largest biomarker discovery effort to identify predictors for depression treatment response.

Because depression is a genetically heterogeneous disorder, smaller studies looking at single markers have not shown much success, Virk told PGx Reporter this week. The iSPOT-D group hopes its more comprehensive approach will identify combinations of genetic and other predictive markers that physicians can use as an objective tool to choose antidepressants more likely to work for individual patients.

"The goal is to enhance the diagnosis, the classification, and the treatment of depression by basically identifying evidence-based markers," Virk said.

Currently, psychiatrists prescribe antidepressant therapy through trial and error, prescribing drugs one by one until they find one that leads to a remission of depressive symptoms. Around 30 percent to 45 percent of depressed patients attain remission with initial treatment, Virk said, while the rest remain at risk for chronic depression as well as issues like suicide, substance abuse, and other serious medical conditions.

The main problem, Virk said, is that physicians don't know which of their patients are going to be in the population that responds to a given drug, and which are not. Resulting treatment schemes see patients cycle from one drug to another, and can be marked by side effects and poor efficacy.

"Right now we don't have any accurate predictor of response to antidepressants … We're hoping this study will identify markers that will provide us with an objective way to determine the magnitude of improvement that can be expected from a particular treatment for a particular patient," she explained.

In iSPOT-D, the Ohio State team has joined several other US centers, as well as groups from Europe, Australia, New Zealand, and South Africa. The centers are evaluating the ability of a variety of markers —including about 300 candidate SNPs, as well as structural and cognitive measures — that might predict or moderate response to three antidepressant medications, escitalopram (Forest Laboratories' Lexapro and generics), sertraline (Pfizer's Zoloft), or venlafaxine (Pfizer's Effexor).

The researchers plan to sample sufficient blood to explore gene expression, proteomic, and metabolomic measures as well, according to a report on the trial protocol published in the journal Trials in 2011, though Virk could not detail any specific plans for proteomic or other analyses.

According to Virk, the trial is enrolling approximately 2,000 patients between the ages 18 and 65. Enrollment began in 2008, and is ongoing, with the study expected to wrap up by the end of 2013. The researchers are following participants for an initial treatment period of eight weeks, and then a follow-up period of six months to a year.

Virk said the centers are dividing the larger cohort into three treatment groups. Approximately 670 patients will be randomized to one of each of the three drugs being studied and matched to another 670 healthy controls.

According to the published protocol and rationale, the researchers plan to use one half of the overall cohort to identify potential predictive markers and the second half to replicate and confirm their results.

The groups are using the Hamilton Rating Scale for Depression to compare depression before treatment and at eight weeks. Some other measures of depressive symptoms will also be checked at two-week intervals between these visits and at additional intervals up to 52 weeks, the group reported.

According to the trial description, all centers are taking a blood sample at baseline for genotyping at a central location in Indiana run by drug development service firm Covance.

The researchers plan to narrow down which, if any, of the candidate SNPs, as well as physical and cognitive measures like brain images, heart rate, and even history of trauma can pick out those patients whose HRSD depression score decreases more than 50 percent on one of the three drugs — a level considered to be "remission" of depression.

The group will also examine secondary endpoints, including self-reported symptoms, side-effects, social functioning, and emotional regulation as measured by a variety of psychological questionnaires.

VIrk said the researchers also hope to discover whether any of the markers can distinguish between different depression subtypes, whether they "normalize with drug treatment but differ according to the drug used," whether genetic or other markers predict outcome not only at the eight-week treatment mark, but over six to 12 months of follow up, and whether any can predict response to placebo or a patient's likelihood to suffer side effects.

"All those things will help us, again, provide more cost-effective care, and also individualize care to each patient," she said.

According to the Trials report, iSPOT-D is sponsored by brain function testing company Brain Resource, which, in addition to sponsoring biomarker research, offers brain training and cognitive assessment services, according to its website.

ISPOT-D joins a number of other projects seeking PGx markers for depression and other psychiatric disorders, few of which have resulted in successful commercial diagnostics.

For example, AssureRx’s GeneSightRx has been one of the more successful psychiatric PGx testing services, recently updating the panel of drugs it covers to 32 medications, 20 antidepressants and 12 antipsychotics (PGx Reporter 1/18/2012).

Virk said the iSPOT-D group hopes its broad approach, considering both physical and genetic markers, will help identify even more accurate predictors to guide antidepressant therapy.

"Out of all those markers, we [hope we] might catch a few that will help us at least to start treatment," Virk said.