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Record W2752779553 · doi:10.1176/appi.pn.2017.pp6a2

Should You Order Genetic Tests Before Prescribing Psychotropics?

2017· article· en· W2752779553 on OpenAlexaboutno aff
Nick Zagorski

Bibliographic record

VenuePsychiatric News · 2017
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmacogenetics and Drug Metabolism
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacogeneticsGenetic testingTest (biology)DosingMedicineGeneticistPsychiatryPsychologyFamily medicinePharmacologyGeneticsInternal medicineBiology

Abstract

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Back to table of contents Previous article Next article PsychopharmacologyFull AccessShould You Order Genetic Tests Before Prescribing Psychotropics?Nick ZagorskiNick ZagorskiSearch for more papers by this authorPublished Online:2 Jun 2017https://doi.org/10.1176/appi.pn.2017.pp6a2AbstractIn some cases, the effects of a genetic variant may be very modest, but pharmacogenetic data may help inform decisions about medication choice and dosing.The debate over whether psychiatrists should incorporate pharmacogenetic testing into clinical practice received attention at APA's Annual Meeting in San Diego. The Biochemist Artist/Shutterstock“I have some colleagues who think we should test routinely and others who say not at all,” Raj Mago, M.D., a psychiatrist in Philadelphia specializing in mood disorders said during a session on managing the side effects of psychotropics. “I don’t think either answer is right. Just like prescribing drugs, not everyone needs it, and you need to match the right test to the right person.”If you wanted to incorporate genetic testing into your decision-making process when prescribing, what might you look for?To help clinicians understand their options in the genetic testing space, Mago described several genetic variants which have commercially available tests, and what sort of information those tests might provide. Tests that assess pharmacokinetics (variants of enzymes involved in drug metabolism) can offer clues about the optimal medication dose for a patient. For instance, if a patient has a variant of the cytochrome P450 (CYP) enzyme CYP2D6, which is known to be a poor metabolizer, it is recommended that clinicians first start them at a lower dose of aripiprazole and then adjust the dose to achieve a favorable clinical response. Other psychotropics influenced by CYP2D6 include the antidepressants fluoxetine and paroxetine, the attention-deficit/hyperactivity disorder medication atomoxetine, and opioids codeine and oxycodone. Mago noted that when ordering genetic tests, it is important to remember that there is a large family of CYP enzymes. “Remember, there’s no such person as a poor metabolizer; people just have deficits in specific CYP enzymes,” he said. For example, while paroxetine is almost exclusively metabolized by CYP2D6, fluoxetine is metabolized by CYP2D6 and metabolized by CYP2C19. Many companies do offer multi-gene test batteries that include all the significant CYPs, but when in doubt, Mago said the Flockhart table offers a valuable resource for tracking known CYP interactions so a doctor can pick the most appropriate test.Another enzyme family to consider when prescribing is the uridine diphosphate glucuronosyltransferases (UGTs), which also metabolize several antidepressants and other psychotropics. Unlike the CYP tests, there is no single test that provides comprehensive UGT genotype data, as different companies have patented tests for different enzymes. Besides pharmacokinetics, genetic tests can also offer insights about pharmacodynamics (how well medications bind to the receptors of patients), Mago said.One newly available test is for the serotonin transporter-linked polymorphic region (5-HTTLPR). This is a highly variable region in the promotor of the serotonin transporter gene, and some people have short versions and some have long versions. Early evidence suggests that people with the long form tend to have a lower risk of side effects from SSRIs than those with short versions. Mago cautioned that current evidence suggests only a modest effect; for example, a large analysis from the STAR*D research study found that 7 percent of people with the long form had serious adverse events compared with 13 percent of people with the short form. Other studies have implicated the HLA allele B*1502 as a marker for carbamazepine-induced Stevens–Johnson syndrome (SJS), a severe skin rash. This allele occurs almost exclusively in patients with ancestry across broad areas of Asia, including South Asian Indians. According to the FDA, “patients with ancestry from areas in which HLA-B*1502 is present should be screened for the HLA-B*1502 allele before starting treatment with carbamazepine.” Mago added that lamotrigine can also cause SJS, possibly via HLA B*1502, so genetic testing may be worthwhile for this drug as well in some patient populations. Evaluating variants of serotonin receptors may also offer clues about risk of potential side effects of medications, Mago said. Previous studies suggest that one polymorphism in the serotonin 2a receptor can identify people more at risk for sexual side effects from antidepressants, while a polymorphism in the serotonin 2c receptor is linked with people more susceptible to antipsychotic-induced weight gain. Because most pharmacogenetic testing is up to physician discretion, clinicians are often faced with the challenge of whether the price of these tests is worth the payoff, Mago noted. “Since this is genetic info, the patient only has to take the test once and the information is valid for their life,” he said, adding that a battery of the most common genetic variants can be done for less than $2,000.“It is important to stress that a genetic test is not a be-all-end-all answer,” James Kennedy, M.D., a professor and co-director of the Brain and Therapeutics Division in the Department of Psychiatry at the University of Toronto, said during a separate session at APA’s Annual Meeting. “It is just one small part of a physician’s decision-making process.” ■ ISSUES NewArchived

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.754
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.145
GPT teacher head0.455
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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