By Rick Nauert PhD Senior News Editor Reviewed by John M. Grohol, Psy.D. on March 29, 2013

Unfortunately, antidepressant drug therapy does not work for everyone. But new research finds that improved identification of genomic predicators that is, how a persons genetic makeup might impact their response to medication will help future treatment of depression.

The National Institute of Mental Healths STAR*D study, the largest and longest study ever conducted to evaluate depression treatment, has determined that only one-third of individuals respond to the first medication prescribed for depression, and that another one-third do not have an adequate response despite being treated with several medications.

Thus, identifying predictors of antidepressant response could help to guide the treatment of this disorder.

A new study, published in Biological Psychiatry, discusses new initiatives for identifying genomic predictors of antidepressant response.

Many previous studies have searched for genetic markers that may predict antidepressant response, but have done so despite not knowing the contribution of genetic factors, saidKatherine Tansey, Ph.D., a psychiatric researcher at Kings College, London.

Our study quantified, for the first time, how much is response to antidepressant medication influenced by an individuals genetic makeup, said Tansey.

For the study, researchers estimated the magnitude of the influence of common genetic variants on antidepressant response using a sample of 2,799 antidepressant-treated subjects with major depressive disorder and genome-wide genotyping data.

They found that genetic variants explain 42 percentof individual differences, and therefore, significantly influence antidepressant response.

While we know that there are no genetic markers with strong effect, this means that there are many genetic markers involved. While each specific genetic marker may have a small effect, they may add up to make a meaningful prediction, Tansey added.

Read the original post:
Genetics Impacts Depression Meds’ Effectiveness

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