Drug Receptor Profiles Matter

Psychiatric TimesVol 37, Issue 4
Volume 37
Issue 4

All current FDA-approved medications for the treatment of schizophrenia antagonize dopamine type 2 receptors-but that is where their similarity ends.

John J. Miller, MD


The classifications of medications into various groups was a helpful organizer in the early years of psychiatry. Identifying a drug as an antidepressant versus an antipsychotic versus an anxiolytic helped us quickly access a medication from a large armamentarium of psychotropics. Established effectiveness allowed clinicians to target a patient’s specific symptoms. In those early days we knew very little about pharmacodynamics, brain circuits, drug metabolism, the possible benefit or harm of a drug’s metabolites, and a drug’s receptor binding profile. The good news is that we have made tremendous strides in understanding each of these drug characteristics. We are now able to make more informed decisions about which drug to use for each patient with a particular diagnosis and specific comorbidities who is being prescribed an array of other prescription medications.

Regrettably, this significant expansion of knowledge about medications gets lost in the continued grouping of drugs by their old classifications. To keep the discussion focused, I explore the class of drugs that we typically call antipsychotics. Significantly, all current FDA-approved medications for the treatment of schizophrenia antagonize dopamine type 2 receptors (DR2)-but that is where their similarity ends. The antipsychotics in this larger grouping have remarkably different, and commonly unique, properties that can provide benefits but may have adverse effects or contraindications. Each of these antipsychotic drugs has a remarkably unique set of receptor binding affinities at a wide range of possible receptors that can assist in making informed choices about which medication to start with, how it will be dosed, how it should be cross-titrated with another antipsychotic, and how to maximize success in managing adverse effects.

The following is a list of some of the receptor properties that differ significantly from one antipsychotic to another:

  • Dopamine 2 receptor antagonist

  • Dopamine 2 receptor antagonist/partial agonist

  • Dopamine 3 receptor antagonist

  • Dopamine 3 receptor antagonist/partial agonist

  • Serotonin receptor antagonist (7 families of serotonin receptors with many subfamilies)

  • Serotonin receptor antagonist/partial agonist

  • Serotonin receptor agonist

  • Muscarinic cholinergic antagonist

  • Histamine 1 antagonist

  • Noradrenergic alpha 1, 2 (with sub-receptors of each) antagonist or agonist

  • Potency of each drug at each receptor: very potent, potent, moderate, weak, very weak

To be clear, we still do not understand all of the drug-receptor properties of any drug for the simple reason that we do not understand all of the receptor genes that reside in the human genome that have not yet been discovered or characterized. Additionally, as we see with the DR2, a gene product can be further processed by post-transcriptional editing (introns and exons) to provide a range of sub-sub-receptors with different binding affinities and circuitry locations (for example, the differing dopamine receptor 2 long [DR2L], which is postsynaptic, versus dopamine receptor 2 short [DR2S], which is presynaptic). To add an additional layer of complexity, each drug that is administered will likely be metabolized to chemically distinct molecules that will have their own unique set of receptor binding properties, which may contribute significantly or negligibly to the pharmacodynamics of the parent drug.

Chlorpromazine, discovered in France in 1950 as a derivative of an antihistamine, became the world’s first antipsychotic medication and was widely used in the 1950s. Interestingly, chlorpromazine has a diverse receptor profile, which includes activity at the dopamine 1, 2, 3, and 4 receptors, serotonin 2, 6, and 7 receptors, histamine 1 receptor, muscarinic acetylcholine 1 and 2 receptors, and the noradrenergic alpha 1 and 2 receptors. Subsequent members of this first-generation antipsychotic group included many drugs with variations of the chlorpromazine receptor profile-significantly all with activity antagonizing DR2s that surfaced as the mechanism necessary for these drugs to treat the positive symptoms of schizophrenia.

When clozapine was FDA approved in 1989, it became a paradigm changer, and it remains our most effective antipsychotic to date with the unique FDA indication for refractory schizophrenia. We still have no idea what receptor property or properties clozapine retains to provide this unique efficacy, but it ushered in a generation of novel medications-second-generation antipsychotics.

Honestly speaking, I disagree with this simplified nomenclature, as this descriptor suggests that all clozapine and post-clozapine drugs differentiate similarly from first-generation antipsychotics.

In my opinion, there are 3 post-clozapine families:

1 Apines: Clozapine, olanzapine, quetiapine, and asenapine. All of these are more potent at the histamine 1 receptor than the D2 receptor, and all (with the exception of asenapine) have significant anticholinergic properties.

2 Idones: Risperidone, paliperidone, ziprasidone, lurasidone and iloperidone. All of these are potent at the D2 receptor, have a wide range of unique binding profiles to various serotonin receptors, and all have some degree of activity at the noradrenergic alpha 1 receptor.

3 Potent antagonists/partial agonists: Aripiprazole, brexpiprazole, and cariprazine. All of these are extremely potent antagonists at the D2 receptor-all three are more potent than all of the other antipsychotics-but also have partial agonism at D2 that renders their pharmacology different than all of the other first- and second-generation antipsychotics, which are pure antagonists. Beyond that, all 3 molecules have very different receptor profiles at other significant receptors.

We cannot generalize antipsychotics into one class of drugs

With this background, I would like to turn your attention to a recent publication in the February 2020 online issue of JAMA Psychiatry: “Effects of Antipsychotic Medication on Brain Structure in Patients With Major Depressive Disorder and Psychotic Features.”1 Voineskos and colleagues analyzed the cortical thickness in gray matter of 72 patients with major depressive disorder with psychotic features. Patients were treated with the sertraline/olanzapine combination for 12 to 20 weeks, including an 8-week period of remission of psychosis, as well as remission or near remission of depression.

This cohort was then randomized in a double-blind fashion to continue the combination regimen or to be switched from olanzapine to placebo (and remain on sertraline) for an additional 36 weeks. For the patients with sustained symptom remission at 36 weeks compared with the placebo-sertraline group, the olanza- pine-sertraline group demonstrated a significant decrease in cortical thickness. A decrease in cortical thickness was also seen in a post-hoc analyses of the patients who relapsed in the placebo-sertraline group compared with the group with sustained remission.

During the several weeks following its online publication, I have read many reviews of this article in various online psychiatric resources, all of which infer that the finding of this study is generalizable to all antipsychotics. Notably, and to the authors’ credit, they recognize a limitation to their study results:

Finally, our data were obtained with 1 specific antipsychotic, olanzapine, and it is possible they do not apply to other antipsychotics. However, based on the wealth of data demonstrating equivalent efficacy among antipsychotics and similar effects of different antipsychotics on brain structure in both animal and human studies, we speculate that our findings are likely to apply across all medications in this class.

The authors should have stopped after their first sentence. The second sentence, in my view, has no merit. “Equivalent efficacy” of olanzapine to other antipsychotics should not support a speculation about brain atrophy as an adverse effect. Moreover, their claim that the generalizability to all antipsychotics is further supported by “similar effects of different antipsychotics on brain structure in both animal and human studies” is also negated by their own claim that:

Concerning animal and uncontrolled human data suggest antipsychotics are associated with change in brain structure, but to our knowledge, there are no controlled human studies that have yet addressed this question.

Yes, they have now published the first controlled human study-but it is with a unique antipsychotic medication, which has a unique receptor profile that is not shared by most other antipsychotic medications. Hence, their study should pave the way for future studies that are randomized, double-blind, and placebo controlled, and which look at antipsychotics with different receptor profiles, or with receptor specific drugs to tease out which receptor(s) activity may be contributing to the decrease in human brain cortical thickness.

One possible explanation: anticholinergic receptor activity

Olanzapine contains anticholinergic receptor antagonism, which its FDA 2013 product insert lists as roughly 4 times weaker than its activity as a DR2 antagonist-relevant activity in the world of receptor binding properties. There is evidence showing that anticholinergic medication is correlated with increased brain atrophy. Risacher and colleagues2 evaluated data obtained from the Alzheimer’s Disease Neuroimaging Initiative of 402 cognitively healthy older adults divided into two groups: individuals taking drugs with medium to high anticholinergic effects (AC+) compared with individuals taking drugs with low to no anticholinergic effects (AC-). The researchers monitored cognition, brain metabolism, and brain atrophy over a mean follow-up of 32 months.

They reported that: “Reduced total cortical volume and temporal lobe cortical thickness and greater lateral ventricle and inferior lateral ventricle volumes were seen in the AC+ participants relative to the AC- participants.”

Chuang and colleagues3 monitored 723 subjects with a mean baseline age of 52.3 years from the Baltimore Longitudinal Study of Aging for a mean follow-up period of 20.1 years. They looked at the impact of long-term anticholinergic drug exposure on brain atrophy in cognitively healthy older adults. They concluded: “Long-term exposure to medications with mild AC (anticholinergic) activity during midlife is associated with increased risk of AD (Alzheimer disease) and accelerated brain atrophy.”


Clearly, much research remains to be done on many fronts. In my view, it is time to upgrade our nomenclature for drug classifications to a system more in line with the proposed neuroscience-based nomenclature (NbN). With this system, a drug’s unique molecular fingerprint would be apparent, and it would facilitate a well-needed transition to a more accurate nosology for drug classifications-one based on mechanism(s) of action rather than artificial and misleading categories.


Dr Miller is Medical Director, Brain Health, Exeter, NH; Editor in Chief, Psychiatric Times; Staff Psychiatrist, Seacoast Mental Health Center, Exeter, NH; Consulting Psychiatrist, Exeter Hospital, Exeter, NH; Consulting Psychiatrist, Insight Meditation Society, Barre, MA.


1. Voineskos AN, Mulsant BH, Dickie EW, et al. Effects of antipsychotic medication on brain structure in patients with major depressive disorder and psychotic features: neuroimaging findings in the context of a randomized placebo-controlled clinical trial. JAMA Psychiatry. February 26, 2020; Epub.
2. Risacher SL, McDonald BC, Tallman EF, et al. Association between anticholinergic medication use and cognition, brain metabolism, and brain atrophy in cognitively normal older adults. JAMA Neurol. 2016;73:721-732.
3. Chuang YF, Elango P, Gonzalez CE, Thambisetty M. Midlife anticholinergic drug use, risk of Alzheimer’s disease, and brain atrophy in community-dwelling older adults. Alzheimer Dement (NY). 2017;3:471-479.

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