Mental Illness and Precision Prescribing

May 3, 2021

Mental illness affects 51.5 million American adults, according to the 2019 National Survey on Drug Use and Health.¹ That’s more than chronic kidney disease (37 million), diabetes (34.2 million), or heart disease (30.3 million). Among those 51.5 million people are 13.1 million people who have serious mental illness, which is defined as a disorder that impedes life activities, such as sleeping, working, or caring for yourself.

 Although mental illness is common, its symptoms and their severity vary greatly among individual patients. The  International Statistical Classification of Diseases (ICD) describes 300 different mental and behavioral disorders. Additional complicating factors make the diagnosis and treatment of mental illness difficult:²

• Patients with the same mental illness diagnosis don’t have the same symptoms, and different disorders sometimes share symptoms.
• Patients commonly have more than one mental illness at the same time. Depression often occurs with anxiety, for example. These comorbidities are likely to be more severe than a single disease, less likely to respond well to medication, and have a higher risk of suicide.
• Patients with the same mental illness don’t respond to the same medication in the same way.

Clearly, mental illness requires a personalized treatment approach.

In most cases in the United States, mental illness treatment involves one or more medications, often in combination with talk therapy. The 2019 National Health Interview Survey, conducted by the National Center for Health Statistics, found that 15.8% of American adults had taken prescription medication for their mental health in the past 12 months.³ But finding the right combination of medications to reduce a patient’s symptoms with minimal side effects often involves some trial and error.

Precision prescribing takes a patient’s unique combination of genes, environment, and lifestyle into account to make the prescribing process more efficient and effective. With this approach, prescribers and pharmacists work together to provide individualized medication plans. Research has identified several factors that are likely to affect how psychiatric medications will work in specific patients.

Genetic Factors

Pharmacogenetics studies variations in DNA and how these variations affect the way patients metabolize drugs. The way a patient metabolizes a drug affects medication dosage. Fast metabolizers may need higher doses to achieve the desired effect; slow metabolizers may need lower doses to avoid severe side effects. A pharmacogenetic test of a patient’s blood or saliva shows which genetic variations a patient has. This test only has to be done once, because the patient’s DNA will not change.

Because the liver is where drugs are metabolized, pharmacogenetic studies focus on genes that code liver enzymes. One of these genes, CYP2D6, helps break down 25% of the most prescribed medications.⁴ The medications listed in the following groups all include pharmacogenomic information related to this gene on their labels.

Table 1: Mental Health Medications with Pharmacogenomic Labeling for CYP2D6

In addition to CYP2D6, these genes are considered “clinically actionable”:⁵ 

• CYP2C19: Like CYP2D6, this gene codes liver enzymes.  It affects how citalopram,  escitalopram (both SSRIs),  and doxepin (a tricyclic antidepressant) are metabolized. All of these medications are used to treat depression. Escitalopram is also used to treat generalized anxiety disorder.
• Human leukocyte antigen: This gene is involved with immune response. Different forms, or alleles, of this gene have implications for patients taking carbamazepine, a drug used to treat bipolar disorder. Patients with the  A type allele (HLA-A)  are at greater risk of having hypersensitivity reactions, such as skin lesions. The B type allele (HLA-B) is associated with an increased risk of Stevens-Johnson syndrome, a serious and potentially fatal disorder.

Lifestyle Factors

Pharmacogenomics studies how gene function is affected by environment changes. Unlike the genes themselves, environmental factors that affect how the genes work can change. This is where a detailed patient history and complete list of the patient’s prescriptions and herbal supplements come in handy. 

Consider just some of the environmental factors that affect the CYP1A2 gene that metabolizes tricyclic antidepressants and conventional antipsychotics:⁴

• Smoking induces CYP1A2 to metabolize the drugs faster and thus lessens their effectiveness. Other CYP1A2 inducers include broccoli, cabbage, cauliflower, and Brussels sprouts.
• Caffeine inhibits CYP1A2 function, potentially causing side effects from the drugs.
• St. John’s wort, an herbal supplement taken to treat depression, affects how CYP1A2 metabolizes drugs.
• Drug-drug interactions with other prescriptions can either inhibit CYP1A2  function,  as in the case of the antibiotic ciprofloxacin, or induce function, as with insulin.

Demographic Factors

The likelihood of taking mental health prescriptions varies depending on sex, race/ethnicity, location, and age among U.S. adults, as does the prevalence of serious mental illness:^1, 3

• Women are more likely to take mental health medication than men, 20.6 % compared with 10.7%. Women also have a higher prevalence of serious mental illness than men, 6.5% compared with 3.9%. 
• A larger percentage of white, non-Hispanic people (19.1%) take medication for mental health than black, non-Hispanic people (11.1%) or Hispanic people (10.3%). Multiracial people have the highest prevalence of serious mental illness (9.3%), followed by Native American (6.7%), white (5.7%), Hispanic (4.9%), black (4%), Asian (3.1%), and Pacific Islander (2.6%).
• People living in rural areas are more likely to take mental health medication than people who live in cities, 18.9% compared with 14.2%.
• Adults older than 44 are more likely to take mental health medication than adults younger than 44, 17.6% compared with 13.6%.  Adults from the ages of 18 to 25 have the highest prevalence of serious mental illness, followed by adults aged 26 to 49 (6.8%), and adults older than 50 (2.6%).

A patient’s age also affects the risk involved in taking psychiatric medications:

• Children, adolescents, and adults between the ages of 18 and 24 have an increased risk of suicidal thoughts and behaviors when taking antidepressants.
• Elderly patients with dementia have an increased risk of stroke when taking antipsychotics.

Actionable Information

Providers and pharmacists need a way to bring all these factors together to help customize a mental health treatment plan for specific patients.  PrecisionRx Advisor™ removes the barriers that stand in the way of precision prescribing. It is the only unified platform that combines patient-specific data from conventional medication therapy management and pharmacogenetic and clinical lab testing with integrated engagement and monitoring workflows to recommend informed improvements to the patient’s prescription plan and overall care. Click here to learn about hc1’s precision prescribing solutions.

References

1. The National Institute of Mental Health. https://www.nimh.nih.gov/health/statistics/mental-illness.shtml
2. Salud García-Gutiérrez, Maria, et al. Biomarkers in Psychiatry: Concept, Definition, Types and Relevance to the Clinical Reality. Frontiers in Psychiatry, May 15, 2020. https://doi.org/10.3389/fpsyt.2020.00432 
3. Terlizzi, Emily P. M.P.H. and Zablotsky, Benjamin, Ph.D. Mental Health Treatment Among Adults: United States, 2019.  National Center for Health Statistics Data Brief No. 380, September 2020. https://www.cdc.gov/nchs/products/databriefs/db380.htm
4. Butler, Merlin G. Pharmamacogenetics and Psychiatric Care: A Review and Commentary. Journal of Mental Health & Clinical Psychology, published April 16, 2018. https://www.mentalhealthjournal.org/articles/pharmacogenetics-and-psychiatric-care-a-review-and-commentary.html
5. Miller, John J. M.D. Psychiatric Pharmacogenomic Testing: The Evidence Base. Psychiatric Times Volume 36, Issue 6, June 19, 2019. https://www.psychiatrictimes.com/view/psychiatric-pharmacogenomic-testing-evidence-base