Mental Health and Genetics: DNA is Central to Treatment

CANMAT has published new guidelines for treating major depressive disorder, commonly known as depression [1]. The document includes the most recent evidence and presents revised, updated recommendations for assessing and managing depression in adults.

In line with scientific advances in personalized medicine, CANMAT is now recommending the use of pharmacogenomic testing when the first antidepressant prescribed is not effective for treating symptoms. Rather than relying on the trial-and-error method to find the right drug and dose, CANMAT recommends that genetic factors be assessed to guide the clinician toward choosing the most appropriate treatment for the patient.

Even though pharmacogenomic tests have been available for several years, this recommendation update speaks to the clinical relevance of these tools when looking for personalized treatments.

Patients do not all react the same to antidepressions and pharmacogenomic testing can often prevent using the wrong drugs. In depression, making use of pharmacogenomics appears to increase the chance of obtaining symptom remission by 41% [2].

Pharmacogenomics is particularly helpful when an antidepressant has side effects or is not effective for treating symptoms, since it helps to determine whether genetic factors may be interfering with how drugs are working. Given that about two out of three patients will not achieve remission with their first antidepressant, there are many people who could benefit from the information provided by pharmacogenomic testing [3].

In addition to dealing with the symptoms of a depressive disorder, patients are sometimes reluctant to take medications, despite the benefits that those drugs might provide.

There are several factors that may inhibit compliance with pharmacological treatment:

Side effects: Drugs’ side effects may be a major barrier to treatment compliance. Unpleasant or intolerable side effects can discourage patients from continuing.

Treatment complexity: Therapeutic regimens that include several medications, varying doses or restrictive schedules may be challenging for patients, particularly if they have other health problems or very full lives.

Forgetting: Remembering to take drugs regularly can be hard, especially for people with busy schedules or cognitive disorders.

Drug costs: The costs of medications may be an obstacle to treatment for many patients, particularly those who have insufficient insurance coverage or limited financial resources.

Lack of understanding: Patients do not always fully understand their medication’s importance and role, which can inhibit treatment compliance. Poor communication from healthcare providers or health illiteracy may underlie the lack of comprehension.

Stigmatization or fear: Some patients may feel embarrassed or ashamed to be taking medications for some conditions, leading them to avoid or discontinue treatment.

Beliefs and attitudes: Patients’ beliefs and attitudes regarding drugs, healthcare providers and the healthcare system—particularly negative perceptions or distrust—may influence their treatment adherence.

Psychological factors: Mental health disorders such as depression or anxiety may impact treatment compliance by altering motivation, mood and cognitive function.

Although it is not a perfect solution, the predictive value of pharmacogenomic testing helps target several of the factors detailed above. Now that this tool has been recommended in the CANMAT guidelines, doctors will be more inclined to use it and offer their patients personalized treatments.

This is promising progress, opening the way to health care that is more appropriate and more effective, and offering hope for a better life to people struggling with mental health problems.

A new era has dawned, so that now healthcare professionals and their patients can benefit from advances in personalized medicine for treating mental health disorders.

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Learn more about pharmacogenomics and how it could be beneficial for your health and well-being.

Pharmacogenomic tests