Gene Variant May Predict Antidepressant Response

Megan Brooks

September 28, 2016

Researchers have identified a genetic variant associated with response to bupropion in patients with major depressive disorder (MDD).

Using data from customers of genetic testing company 23andMe, Inc, they found that for individuals with the genetic variant rs1908557, the odds were higher that treatment with bupropion would be ineffective.

They also identified several "gene sets" associated with long-term depression, circadian rhythm, and the vascular endothelial growth factor pathway that were enriched in the bupropion response analysis.

"The most interesting finding is that there were relatively more genetic differences between bupropion responders and nonresponders in genes implicated in biological processes important for patients with major depressive disorder [than genes elsewhere in the human genome]," first author Qingqin Li, PhD, scientific director, Neuroscience Integrative Solutions and Informatics, Janssen Research & Development, LLC, Titusville, New Jersey, told Medscape Medical News.

"Those biological processes included sleep disturbance and neurogenesis. These together with the 'heritability' [ie, the proportion of disease risk that could be explained by genetic risk factors] similarity between self-report and clinically ascertained cohorts reported by consortium efforts suggest that phenotype based on self-report information may prove informative for ascertaining selected treatment outcome and disease status and help to advance the understanding of difference in treatment response," said Dr Li.

The study was published online September 13 in Translational Psychiatry.

Pinpointing the Right Drug

There are roughly 30 antidepressants available for MDD. Response to treatment varies in time to onset of benefit, overall efficacy, and duration of effect. Genetic variability may contribute to the differences in drug-specific, class-specific, or antidepressant-wide treatment nonresponse/resistance, the study team notes in their article.

They analyzed self-reported information from 238,000 23andMe customers, including roughly 48,000 who reported being treated for depression. Using phenotype and genotype data, they conducted a genome-wide association study (GWAS) on four groups of phenotypes: non-treatment-resistant depression vs treatment-resistant depression; selective serotonin reuptake inhibitor responders vs nonresponders; citalopram/escitalopram responders vs nonresponders; and bupropion responders vs nonresponders.

Of a total of 12 GWAS analyses performed, only the bupropion responders vs nonresponders analysis yielded a locus that reached the genome-wide significance threshold, they report. Each copy of the rs1908557-C allele was associated with higher odds of not responding to bupropion (odds ratio, 1.35). "The frequency of C allele was relatively common (minor allele frequency = 25%) in the study population," the investigators report.

"This finding will ultimately require replication in clinically ascertained samples to further dissect the genetic basis of treatment response to bupropion among depression patients," they write. "The biological significance of rs1908557 is unknown except that rs1908557 is also marginally associated with two brain regions known to exhibit volumetric difference between MDD subjects and healthy controls," they add.

They further acknowledge that "genetic variants alone are unlikely to deliver clinically actionable predictive diagnostic tests. A more comprehensive approach using a composite signature of predictors ultimately may be required to predict treatment outcome to a particular drug class with sufficient sensitivity and specificity to warrant its use in the clinic."

"Our studies in this area are ongoing," Dr Li told Medscape Medical News. "Additional data collected could be used to augment the current analysis by increasing the study sample size, replicate the reported significant finding, or to study additional class of antidepressants when the sample size becomes larger. Other clinical samples being collected could also help to replicate the reported findings."

Unique Dataset

"I think this is a good paper," Scott Russo, PhD, associate professor of neuroscience, Icahn School of Medicine at Mount Sinai in New York City, noted in an interview with Medscape Medical News.

"What's interesting about using 23andMe customers is that I think it will include populations of people that typically wouldn't take part in a research study, and so that data – kind of like Facebook mining – could reach a group of potential participants that are underrepresented in traditional research settings," explained Dr Russo, who was not involved in the study. "For genomics and genetics and understanding linkages to particular diseases or treatment responses, that would be a huge benefit in enriching for patients who you have low power for in your more traditional studies.

"Clinically," Dr Russo said, "what we need the most is to be able to predict who is going to respond to what treatment. This is a first step toward that." One major goal in psychiatry, Dr Russo added, is to incorporate biological diagnostic criteria and be able to use that to predict not just disease but also treatment response.

The genotype-phenotype association analysis was funded by Janssen Research and Development, LLC. Four of the five authors are employees of the company. The other author is an employee of 23andMe. Dr Russo has received funding from Janssen Pharmaceuticals to conduct research in the past but is not currently funded by Janssen.

Transl Psychiatry. Published online September 13, 2016. Full text

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