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  • Parenting, Pregnancy, and Prevention (March)
  • A Second Look at Genetic Testing

A Second Look at Genetic Testing

The Carlat Psychiatry Report, Volume 17, Number 3, March 2019
https://www.thecarlatreport.com/newsletter-issue/tcprv17n3/

From The Carlat Psychiatry Report, March 2019, Parenting, Pregnancy, and Prevention

Issue Links: Learning Objectives | Editorial Information | PDF of Issue

Topics: Free Articles | GeneSight | Genetic Testing | Pharmacology

Print Friendly, PDF & Email

Chris Aiken, MDChris Aiken, MD.

Editor-in-Chief of The Carlat Psychiatry Report. Practicing psychiatrist, Winston-Salem, NC.

Dr. Aiken has disclosed that he has no relevant financial or other interests in any commercial companies pertaining to this educational activity.

Genetic tests are marketed with a bold claim: that a handful of genes can predict medication response. AssureRx’s GeneSight is the most popular of these tests, and in 2015 we reviewed the evidence behind its panel. In short, it was lacking, but the company has just released new data that may move it a little closer to the mainstream.

What’s in the test
GeneSight looks at two areas where genetics can influence medication response:

  1. Pharmacokinetics. Around 20%–30% of people have genetic variations in their metabolic enzymes that can lead to levels of many psychiatric medications that are abnormally high (ie, slow metabolizers) or abnormally low (ie, fast metabolizers).
  2. Pharmacodynamics. While pharmacokinetics is about serum levels, pharmacodynamics is about the brain’s response to medications, which may be shaped by genetics.

GeneSight uses this information to create a stoplight with three categories of recommendations: Green (no worries—go ahead and prescribe this medication), Yellow (proceed with caution), and Red (best to avoid). Other companies present their results in a similar style, but each company’s results are driven by different, proprietary algorithms, which limits the ability of independent investigators to evaluate their validity. In other words, we’re stuck with industry-supported trials, and so far GeneSight has the largest number of them.

What we know so far
Before this new study was released, ­GeneSight’s clinical data had run into a brick wall. The positive studies were poorly designed, while the well-designed studies were negative. Two open-label, non-randomized studies with a total of 209 subjects suggested that GeneSight improved outcomes in depression. However, a randomized, double-blind trial failed to replicate that benefit (Zeier Z et al, Am J Psychiatry 2018;175(9):873–886). That negative study was small, involving 49 subjects, so the company undertook a larger study to see if they could demonstrate the value of their test.

A new study
GeneSight’s latest study is the largest to date, involving 1,167 subjects with moderate to severe treatment-resistant depression. They were randomized to receive antidepressant therapy that was guided either by GeneSight or by the clinician’s usual care. Most patients had failed at least 3 antidepressants, although only 1 failure was required for study inclusion. After 8 weeks, there were no significant differences between the two groups on the primary outcome measure, which was improvement on the Hamilton Depression Rating Scale (HAM-D). Although the study failed on the primary measure, results were marginally positive on secondary outcomes of response (≥ 50% improvement on the HAM-D, achieved by 26% in the GeneSight group vs 20% in the controls) and remission (final HAM-D ≤ 7, achieved by 15% in the GeneSight group vs 10% in the controls) (Greden JF et al, J Psychiatr Res 2019;111:59–67).

How impressive are these results?
A glance at GeneSight’s new brochure would have you believe the results are quite impressive. The secondary outcomes are on the cover, magnified to accentuate a small difference. In reality, you’d need to test 20 patients with ­treatment-resistant depression to bring 1 patient to remission. The results look a little better when limited to those patients who were switched from medications that were poorly matched with their genes to those that, according to the test, were a better fit. In this group, you’d need to test 8 patients to bring 1 to remission. That’s still fairly modest, and keep in mind that only 1 in 5 patients entered the study on medications that did not match their genes.

A bigger problem is that the primary measure was negative, and in a large study like this, such a failure is fairly definitive. Secondary measures are meant to explore possibilities, not confirm the truth, because every time one is added, it increases the chance of a false positive. No one should boast about secondary measures, and these aren’t even much to boast about.

Also, the study was not truly double-blind, a flaw shared by all the controlled trials in this field. Patients and raters were blinded to the presence of genetic testing, but the doctors who chose the antidepressants were not. It’s possible that these physicians conveyed a little more enthusiasm about their choices when they knew those choices were guided by a genetic test.

Other contenders
GeneSight is one of over 40 commercially available tests. Three of their competitors have randomized controlled trials: NeuroIDGenetix, Neuropharmagen, and GeneCept.

NeuroIDGenetix uses a genetic panel similar to GeneSight’s and just released a 12-week double-blind randomized controlled trial in 685 patients with depression or anxiety. Their paper boasts positive results, but they selectively reported the data, including only half of the sample (those with moderate to severe depression) in their final results (Bradley P et al, J Psychiatr Res 2018;96:100–107).

Neuropharmagen employs a much broader array of genes in their algorithm and recently released two major studies. As with GeneSight, the more rigorous the study, the less impressive the results. Neuropharmagen has two randomized controlled trials in depression, one from Korea (n = 100) and the other from Spain (n = 316). The Korean study was positive across the board, but it was single-blind; raters were not blinded to the use of the test. The Spanish study was double-blind, but like the GeneSight trial, it was positive only on secondary measures (Pérez V et al, BMC Psych 2017;17:250; Han C et al, Clin Psychopharmacol Neurosci 2018;16:469–480).

GeneCept takes a different approach, focusing on genes that regulate the transport of medications across the blood-brain barrier. If that transport is slow, higher doses may be needed. GeneCept’s panel only tells us about the dosing of medications, not their selection. However, it is the only test that has a positive, well-designed study without major flaws. In their 12-week randomized controlled trial of 148 patients with depression, the remission rate was 2.5 times greater in the gene-guided group: 28% vs 72% (Singh AB, Clin Psychopharmacol Neurosci 2015;13:150–156).

A few good tests
These clinical trials test proprietary algorithms, with results that are promising but not yet definitive. There’s another way to use genetic testing, though—you can skip the summary and look at the individual tests. Two groups, the Clinical Pharmacogenetics Implementation Consortium (CPIC) and the FDA, keep a running tally of the drug-gene interactions that are valid and reliable. So far only a handful of pharmacokinetic genes have met their standards: CYP2C19, CYP2D6, and, with ­flibanserin (Addyi), CYP2C9. The groups have also weighed in on which medications are reliably altered by those genes, and they’re listed in the “Actionable Drug-Gene Interactions” table below. These are the drug-gene interactions worth paying attention to in a genetic panel.

Table: Actionable Drug-Gene Interactions

Table: Actionable Drug-Gene Interactions

Click to view full-size PDF.

What about pharmacodynamic genes? The serotonin transporter gene is the most researched of these and is part of the GeneSight panel. Supposedly, the short version of this gene predicts lower response and more side effects with SSRIs, but the actual evidence on those points is mixed. The data on side effects did not hold up in a meta-analysis (Crawford AA et al, Eur Neuropsychopharmacol, 2013;23:1143–1150). For response to SSRIs, one meta-analysis found no relationship, while another concluded that the association was weak and only held up in European patients (Porcelli S et al, Eur Neuropsychopharmacol 2012;22:239–258; Taylor MJ et al, Biol Psychiatry 2010;68:536–543).

TCPR Verdict: Most genetic tests add a marginal benefit that is barely detectable in clinical trials. We don’t recommend them for routine use, but they may have a role in patients with moderate to severe depression who have failed multiple antidepressants. GeneCept has promising data to guide antidepressant dosing, but not selection, and that study needs confirmation. When interpreting genetic tests, take heed of the drug-gene interactions supported by good evidence, mainly the CYP2D6 and CYP2C19 genes.

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  • Natural Medications in Psychiatry (May)
  • Posttraumatic Stress Disorder (April)
  • Treatment of Alcoholism (March)
  • Battle of the Atypicals (February)
  • Antidepressant Roundup, 2004 (January)

2003

  • Research Methods in Psychiatry (December)
  • Antidepressants in Children (November)
  • The Treatment of Dementia (October)
  • Bipolar Disorder, Part II: The Novel Anticonvulsants (September)
  • Bipolar Disorder: The Basics (August)
  • Drug-Drug Interactions in Psychiatry (July)
  • Managing Antidepressant Side Effects (June)
  • Antidepressants in Pregnancy and Lactation (May)
  • ADHD: Medication Options (April)
  • Panic Disorder: Making Treatment Work (March)
  • Atypical Antipsychotics in Clinical Practice (February)
  • Medication Treatment of Depression (January)

2019

  • Autism in Children and Adolescents (November/December)
  • Depression in Children and Adolescents (May/June/July/August)
  • Substance Use in Children and Adolescents (September/October)
  • Trauma in Children and Adolescents (March/April)
  • Anxiety in Children and Adolescents (January/February)

2018

  • Psychotropic Risks in Children and Adolescents (May/June)
  • ADHD in Children and Adolescents (November/December)
  • Depression in Children and Adolescents (September/October)
  • Autism in Children and Adolescents (July/August)
  • Anxiety in Children and Adolescents (March/April)
  • Suicide in Children and Adolescents (January/February)

2017

  • Adolescents (November/December)
  • ADHD in Children and Adolescents (September/October)
  • Psychosis in Children and Adolescents (August)
  • PANDAS, PANS, and Related Disorders (June/July)
  • Marijuana in Children and Adolescents (May)
  • Tourette’s and Other Tic Disorders in Children and Adolescents (March/April)
  • Autism in Children and Adolescents (January/February)

2016

  • Gender Dysphoria in Children and Adolescents (November/December)
  • Technology Issues With Children and Adolescents (September/October)
  • Mood Dysregulation in Children and Adolescents (July/August)
  • Eating Disorders in Children and Adolescents (May/June)
  • Conduct Disorder in Children and Adolescents (April)
  • Sleep Disorders in Children and Adolescents (March)
  • ADHD in Children and Adolescents (January/February)

2015

  • Antidepressant Use in Children (November/December)
  • Foster Care and Child Psychiatry (September/October)
  • Autism (July/August)
  • Trauma (May/June)
  • Anxiety Disorders (April)
  • Schools and Psychiatry (March)
  • Emergency Psychiatry in Children (January/February)

2014

  • Antipsychotics in Children (December)
  • ADHD (November)
  • Gender and Sexuality (September/October)
  • Psychotic Symptoms (Summer)
  • Medication Side Effects (May)
  • Food and Mood (April)
  • Learning and Developmental Disabilities (February)

2013

  • Complex Practice Issues (December)
  • Diet and Nutrition (November)
  • Child Psychiatry in DSM-5 (August/September)
  • Medication Side Effects and Interactions (June/July)
  • Problematic Technology (March/April)
  • Autism Spectrum Disorders (January/February)

2012

  • Bipolar Disorder (December)
  • Substance Abuse (October/November)
  • Transitional Age Youth (July/August)
  • Rating Scales (May/June)
  • Eating Disorders (March/April)
  • Behavioral Disorders (February)

2011

  • Treatment of Anxiety Disorders (December)
  • Trauma (November)
  • Bullying and School Issues (October)
  • Hidden Medical Disorders (August)
  • OCD and Tic Disorders (June)
  • Suicide and Non-Suicidal Self Injury (April)
  • Sleep Disorders (March)
  • ADHD (January)

2010

  • Use of Antipsychotics in Children and Adolescents (December)
  • Learning and Developmental Disabilities (October)
  • Major Depression (September)
  • Treating Children and Families (July)
  • The Explosive Child (May)

2019

  • Dual Diagnosis in Addiction Medicine (May/June)
  • Medical Issues in Addiction Practice (November/December)
  • Alcohol Addiction (September/October)
  • Legal Issues in Addiction Medicine (July/August)
  • Traumatic Brain Injury and Addiction (March/April)
  • Board Certification in Addiction Medicine (January/February)

2018

  • Opioid Addiction (November/December)
  • Addiction in Older Adults (October)
  • Sleep Disorders and Addiction (September)
  • Adolescent Addiction (July/August)
  • Pain and Addiction (May/June)
  • Cannabis and Addiction (March/April)
  • Stigma and Addiction (January/February)

2017

  • Pregnancy and Addiction (November/December)
  • Detox (Sepember/October)
  • Dual Diagnosis (August)
  • Alternatives to 12-Step Programs (June/July)
  • Recovery (May)
  • Psychiatric Uses of Street Drugs (March/April)
  • Sex Addiction (January/February)

2016

  • Prescription Drug Monitoring Programs (PDMPs) (November/December)
  • Addiction in Health Care Professionals (September/October)
  • Dialectical Behavior Therapy in Addiction (August)
  • Motivational Interviewing (June/July)
  • Benzodiazepines (May)
  • Opioid Addiction (March/April)
  • Families and Substance Abuse (January/February)

2015

  • The Twelve Steps (November/December)
  • Designer Drugs (September/October)
  • Residential Treatment Programs Decoded (July/August)
  • Nicotine and E-Cigarettes (June)
  • Drug Screening (April/May)
  • Integrating Therapy and Medications for Alcoholism (March)
  • Detoxification Protocols (January/February)

2014

  • Behavioral Addictions (December)
  • Risk and Reimbursement (November)
  • Stimulant Abuse (September/October)
  • Self-Help Programs (June)
  • Opioid Addiction (May)
  • Coping with Bad Outcomes (March)
  • Change Management in Addiction Treatment (January/February)

2013

  • Cocaine Addiction (December)
  • Relapse Prevention (November)
  • Cannabis Addiction (August/September)
  • Addiction in DSM-5 (June/July)
Editor-in-Chief

Chris Aiken, MD

Dr. Aiken is the director of the Mood Treatment Center in North Carolina, where he maintains a private practice combining medication and therapy along with evidence-based complementary and alternative treatments. He has worked as a research assistant at the NIMH and a sub-investigator on clinical trials, and conducts research on a shoestring budget out of his private practice.

Full Editorial Information

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