Dr. Wall is instructor of psychiatry and consultant in child psychiatry and Dr. Swintak is instructor in psychiatry and senior associate consultant in child psychiatry, both in the Department of Psychiatry and Psychology at the Mayo Clinic in Rochester, Minnesota. Ms. Oldenkamp is a medical student at the Mayo Medical School in Rochester.

Disclosure: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Christopher A. Wall, MD, Instructor of Psychiatry, Consultant–Child Psychiatry, Dept of Psychiatry and Psychology, Mayo Clinic, 200 1st St, SW, Rochester, MN 55905; Tel: 507-284-3352; Fax: 507-533-5353; E-mail: wall.chris@mayo.edu.


Historically, clinicians have had few resources beyond empiric tools derived from population-based treatment algorithms and patient/family interviews to inform the “best choice” for psychopharmacologic intervention. Previously unappreciated interindividual variance in activity of cytochrome P450 enzymatic activity can lead to abnormal metabolism of many psychotropics and poor outcomes. Fortunately, advances in our understanding and application of psychiatric pharmacogenomic information have the potential to improve the quality of medical care for children at the level of the individual prescription.

Focus Points

• Advances in pharmacogenomics have the potential to improve the quality of medical care for children at the level of the individual prescription.
• Nearly 80% of all drugs in use today, along with most psychotropics, are metabolized via testable metabolic pathways.
• Children and adolescents with metabolic polymorphisms may be at greater risk for adverse drug events than children with normal metabolism.
• Pediatric psychotropic prescribers must consider treatment-resistant patients as potential abnormal metabolizers.



A large number of children and adolescents presenting for health care are affected by mental illness and many require psychotropic medications as a component of their overall care.1,2 Despite increasing choices in medication management, many of these patients still experience poor outcomes related to inadequate medication response and significant adverse drug events (ADEs).3 Given ongoing shortages in the specialty of child and adolescent psychiatry,4 the considerable challenge of prescribing psychotropics in the pediatric population is often managed by adult psychiatrists, family physicians, and pediatricians. In considering whether a medication is the “right” one for a given patient, all clinicians must weigh not only issues such as the potential for side effects, family responses to similar psychotropic medications, and the nature and intensity of the patient’s illness, but also psychosocial concerns. This is a process which is complicated by the knowledge that an incorrect choice could result in intolerable side effects, poor efficacy, and ultimately—perhaps most importantly—a negative view towards medication that may have proved helpful. Lack of efficacy and ADEs are frequently cited as reasons for noncompliance in pediatric psychopharmacology.

Currently, children who are treated without the benefit of individualized molecular genotyping have only a 60% chance of successful long-term treatment.5 Fortunately, advances in our understanding and application of individual pharmacogenetic profiles have the potential to improve the quality of medical care for children at the level of the individual prescription.6 Pickar7 has suggested that there is no specialty where the need for pharmacogenetics seems more compelling than for psychiatry. Psychiatric pharmacogenomics is an emerging tool to assist clinicians in developing strategies to personalize treatment and tailor therapy to individual patients, with the goal of optimizing efficacy and safety through better understanding of genetic variability and its influence on drug response. This article provides discussion of the role emerging pharmacogenomic advancement is playing in the clinical practice of individualized psychopharmacology: moving away from “trial and error” prescriptions to individualized prescribing. The article also highlights the growing literature and adoption of pharmacogenomic principles guiding modern psychotropic prescribing practices focusing on the pediatric population.


Background of Psychiatric Pharmacogenomics

Psychiatric pharmacogenomics is the study of how gene variations influence the responses of a patient to treatment with psychotropics. The most commonly studied cytochrome P450 (CYP) enzymes include 2D6, 2C19, and 2C9. Polymorphisms and gene duplications in these enzymes account for the most frequent variations in phase I metabolism of drugs since nearly 80% of all drugs in use today, along with most psychotropics (Tables 1 and 2),8 are metabolized via these pathways.9 It should also be noted that genetics may account for 20% to 95% percent of variability in drug disposition and effects.10


Historic and current literature divides metabolic phenotypes into four basic categories. These categories presented from least to most efficient metabolism are as follows: poor metabolism (PM; essentially no metabolism at a given enzyme pathway), intermediate metabolism (IM), extensive metabolism (EM; essentially “normal” metabolism), and ultra-rapid metabolism (UM). For the purpose of discussion, this article will highlight safety and efficacy concerns related to the 15% to 25% of pediatric patients that are either PM or UM metabolizers.11


Safety and Efficacy in Abnormal Metabolizers

The two primary tenets considered in all pediatric prescriptions are safety and efficacy, and both can be more precisely addressed through pharmacogenomics. “Safety pharmacogenomics” aims to avoid ADEs and side effects by identifying individuals who are likely to have difficulty with certain medications due to either increased activity of an enzymatic pathway (UMs), or lack of activity (PMs). “Efficacy pharmacogenomics” attempts to predict an individual’s likely response to a medication at the outset of treatment.12

Interindividual variance of activity of CYP enzymes can lead to abnormal metabolism of most antidepressants (Table 1) and antipsychotics (Table 2). These medications have been associated with a variety of ADEs, ranging from milder side effects, such as activation, irritability, sexual dysfunction, and sedation, to more significant ADEs, such as weight gain, extrapyramidal symptoms, metabolic syndrome, hyperprolactinemia, manic-induction, neuroleptic malignant syndrome, and even suicidality.13 Children and adolescents with polymorphisms leading to abnormal drug metabolism may be at greater risk for some of these ADEs than children with normal metabolism, as medications administered at normal therapeutic doses to poor metabolizers may result in toxicity, and consequently ADEs. Conversely, UMs may not attain therapeutic plasma levels on typical therapeutic doses of medications and the treatment may fail or lead to rapid conversion of prodrug to potentially toxic active metabolites.

Table 313-51 includes a list of ADEs that have been linked to abnormal metabolism of psychotropics by at least one study involving abnormal metabolizers. As pharmacogenomic testing is a relatively new technology, not many studies have been performed investigating these links, but identifying the at-risk population in advance could do much to positively affect quality of life, increase compliance with medications, and even circumvent death in rare cases. Pharmacogenomic testing has the potential to offer a more complete, individualized risk profile enabling tailored choices of medication with doses appropriately adjusted for individual metabolism and advanced screening for the propensity of certain undesirable effects.


Safety and Efficacy Implications in Poor Metabolism

Weight Gain and Metabolic Syndrome

There is no doubt that weight gain can be detrimental to a young person’s physical and mental health and can exacerbate problems with self-esteem during all developmental stages. Obesity, which is common among schizophrenic patients,52 may be further exacerbated by antipsychotics. It has been shown that decreased metabolism due to variations in several CYP genes may contribute to a patient’s risk profile while taking an antipsychotic. For example, decreased metabolism at CYP1A2, which is known to be involved in the metabolism of some antipsychotics, is associated with increased risk for weight gain and a cluster of clinical features including increased visceral adiposity, hyperglycemia, hypertension, and dyslipidemia known as “metabolic syndrome.”53 Prevalence of metabolic syndrome is higher in women than it is in men as demonstrated in the Clinical Antipsychotic Trials of Intervention Effectiveness schizophrenia trial.53 Lower activity of CYP1A2 may also contribute to the risk for metabolic syndrome by leading to increased serum concentrations of antipsychotics at standard doses. Children, especially young females, may be more susceptible to weight gain while on antipsychotics,53-55 and weight gain may lead to noncompliance and subsequent relapse.52-56

All of this evidence suggests that pediatric patients are likely to be at increased risk of weight gain and metabolic syndrome if carrying polymorphisms associated with decreased or absent 1A2 activity. Identifying poor metabolizers at this and other genes associated with atypical antipsychotic metabolism could allow a physician to be better informed of all risks when prescribing, and heighten awareness related to early signs of metabolic syndrome or weight gain. This may be especially pertinent to young female patients, who appear to carry the most risk.


Extrapyramidal Symptoms

Extrapyramidal symptoms (EPS) are frequent and serious acute adverse reactions to antipsychotics. These symptoms include pseudoparkinsonism, acute dystonia, akathisia, and tardive dyskinesia,34 which may be permanent even after removal of the drug.

Several hypotheses and studies indicate that PM at CYP2D6, which metabolizes several of the typical and atypical psychotropics, may increase the risk of developing EPS. Poor CYP2D6 metabolizers are likely to have higher than average plasma concentrations of neuroleptics with an increased risk for developing EPS, including tardive dyskinesia.14,34,57-59 PM or inhibition of CYP2D6 may be linked to the induction of EPS. CYP2D6 in the brain is involved in the metabolism of dopamine and has a possible functional association with the dopamine transporter.59,60 Several selective serotonin reuptake inhibiters and tricyclic antidepressants inhibit CYP2D6, as do a number of non-psychotropic drugs such as quinidine. Methylphenyltetrahydropyridine, a dopamine neurotoxin able to produce Parkinsonism, is metabolized by 2D6 and is also a 2D6 inhibitor. Vandel and colleagues59 concluded that inhibition of CYP2D6 may be involved in the genesis of EPS observed in treatment with 2D6 substrate psychotropics.

It follows that poor CYP2D6 metabolizers may be at increased risk for EPS while on certain antidepressants due to high plasma levels.59 Indeed, it has been shown that there is a significant association between EPS and the CYP2D6*4 and CYP2D6*6 polymorphisms that are both associated with the poor metabolizer phenotype.61,62 Furthermore, there may be a relationship between the degree of impaired CYP2D6 activity and the severity of EPS during neuroleptic treatment.34 One study14 demonstrating that the development of EPS or tardive dyskinesia while on antipsychotic medication is significantly more frequent among PMs than among matched IM and EM patients, also found a significantly higher prevalence of noncompliance among the same PM patients. These findings highlight the importance of identifying those at greater risk for experiencing these serious ADEs.


Neuroleptic Malignant Syndrome

Neuroleptic malignant syndrome (NMS) is a life-threatening ADE associated with antipsychotics, antidepressants, and other psychotropics. Signs of NMS include hyperthermia, EPS, altered consciousness, fluctuating blood pressure, incontinence, and dyspnea.48,63,64 While some studies were unable to find a significant link between reduced function of CYP2D6 and NMS,65,66 more recent case studies suggest pharmacogenomic factors cannot yet be excluded as risk factors for this serious condition. In two separate case studies, four patients who developed NMS were later determined to have mutations in CYP2D6 conferring the PM phenotype.48 It was concluded that while not all NMS patients have this poor metabolizer phenotype, poor metabolizers at CYP2D6 may be at increased risk for developing NMS.49



Conventional antipsychotics and certain atypical antipsychotics, such as risperidone, can cause significant elevations in prolactin.53 For risperidone, increases in prolactin levels are dose related.53,67 Though no studies have yet been conducted to show a link between PM phenotypes and ADEs related to hyperprolactinemia, this link remains not only possible, but an important consideration in the pediatric population. Amongst other potential developmental concerns, complications from early hyperprolactinemia may include bone loss, which in turn could lead to significant consequences upon reaching adulthood. Furthermore, if this increase in prolactin is dose related, PMs may have elevated risk as they may experience higher serum concentrations of poorly metabolized medication.


Additional Considerations

Prescribers should also bear in mind that over sedation, postural hypotension, and cardiovascular complications may be additional significant concerns in poor metabolizers.68 Likewise, as clinicians follow their natural tendency to optimize dosing in their treatment of psychiatric symptoms, it may be helpful to remember that, in the PM population, so called “somatic symptoms” associated with psychiatric diagnoses (and subsequent treatment) may in fact be medication intolerance exacerbated by dose titration. Without knowledge of the patient’s metabolic phenotype, the clinician must “guess” as to the cause of these symptoms and may incorrectly conclude that the patient is just “anxious” or “dramatic.” Furthermore, the clinician must also wonder whether or not the patient will be able to adequately tolerate the next medication choice.


Safety and Efficacy Implications in Ultra-Rapid Metabolism

UMs present their own set of treatment challenges as they may not attain therapeutic plasma levels on normal doses of medications, and thus treatment may have a higher propensity to fail.69 For example, a recent Swedish autopsy study13 found that among those who died of suicide, there was a higher number carrying >2 active CYP2D6 genes (UM phenotype) as compared with those who died of natural causes. Postulated explanations for this finding include accumulation of higher levels of metabolites at a faster rate which is a known risk of UM. This buildup may lead to adverse drug reactions if the metabolite is active or toxic. It could also be argued that in this population, UMs did not reach the desired therapeutic concentration of their prescribed medications and thus had not been treated effectively. This hypothesis is supported by Kawanishi and colleagues43 who found UMs as more likely to fail to respond to antidepressants. The ultra-rapid metabolizers in the study also had the worst scores on the Hamilton Rating Scale for Depression leading the authors to conclude that ultra rapid metabolism may be a risk factor for persistent mood disorders.

Case studies in UMs suggest that diphenhydramine may be converted to a compound which causes paradoxical excitation due to the abnormally high CYP2D6 activity.41 More serious consequences might be seen in children treated with other medications like codeine whose ultra-rapid conversion might result in toxic accumulation of morphine leading to death.23 It follows that UMs could be at increased risk of ADEs from higher levels of toxic or active metabolites from psychotropics.



To date, much of the available literature on pharmacogenomic testing in the pediatric population has focused on the spectrum of efficacy related to cancer treatments.70-75 Impressive results in leukemia remission rates have been described as partly due to advancements in pharmacogenomically derived individualized prescribing practices. Cheok and colleagues70 highlighted the progress made in the treatment of acute lymphoblastic leukemia in children noting the disease as being lethal 4 decades ago to current cure rates exceeding 80%. This progress is largely due to the optimization of existing treatment modalities rather than the discovery of new antileukemic agents. The literature regarding the pharmacogenomics of asthma treatment and research design has also been quite active in the pediatric population in the past few years.76-83 In both cancer and asthma research, there are clear outcomes and endpoints to define treatment response and the role that interindividual variability plays.

Historically, the process of initiating psychopharmacologic agents in the child and adolescent population has been empirically based and one in which the clinician considers many variables including age, gender, access to health care, and ability to remain compliant with the proposed treatment. Frequently factored into this consideration are quasi-genetic questions relating to family history of illness as well as family history of medication response. Until very recently, the use of family history has been the only tool available to better understand genetic makeup and its resultant interplay with efficacy and ADEs. In fact, as early as the 19th century, Holmes84 commented that, “All medications are directly harmful; the question is whether they are indirectly beneficial.” Fortunately, unlike in Holmes’ day, we now have the potential capability to resolve that very question; pharmacogenomic testing can help determine in advance whether an individual will respond favorably. Ongoing central nervous system maturation coupled with an increased risk for ADEs makes the utility of this advance most relevant in pediatric psychopharmacology.

Though most prescribing in pediatric psychiatry is still off label, treatment algorithms do currently exist for most classes of psychotropics. Unfortunately, none of these algorithms base their recommendations on psychiatric pharmacogenomics. Furthermore, since dosing recommendations are based on “normal” metabolizers, they do not include the estimated 15% to 25% of the population who is either UMs (and therefore at much higher risk for resultant noncompliance due to never reaching therapeutic and/or beneficial levels) or poor with non-compliance resulting from ADEs. These outliers, who frequently end up in treatment-resistant categories of patients, might have entirely different outcomes if medication management were tailored to their genetic—and therefore most fundamental—needs.

When considering the “stakes” involved in the early patient-physician-family relationship, it is clear that prescribing with improved confidence, and less risk of ADEs, will pay significant dividends. For example, if a clinician thoughtfully considers not only the symptoms involved in the patient’s illness process, but also the likelihood that the patient will experience difficulties with certain medications, the patient and family cannot help but be appreciative of the efforts involved at defining their particular risks. This transparency of process and subsequent conversations about the role for medications will allow for greater trust and a sense of improved objectivity.

Widespread adoption of pharmacogenomic testing will be hampered by several factors including costs, limited sample sizes in research reports, and ingrained practice habits fueled by understandable skepticism and access challenges. Each of these issues will need to be individually addressed and overcome in the foreseeable future. Several academic medical centers are incorporating this form of testing into the comprehensive biopsychosocial workup and results appear promising.11,85 Today, the cost of the genotyping of a single gene varies between $300–$700 depending upon the complexity of the variants that are being identified. Fortunately, panels of informative genes can now be ordered for between $800–$1,500. With the rapid improvement in sequencing technologies that is now occurring, these costs will inevitably decrease in the near future.

As psychiatric illnesses are increasingly recognized and treated in the pediatric population, clinicians now have access to an emerging set of pharmacogenomic principles to guide their prescribing practices. The primary principle is to use pharmacogenomic testing to increase the safety of psychotropics. A second principle is to use testing to identify medications that are unlikely to be effective. The ultimate goal of pharmacogenomic testing is to find the “right medication” on the first try. As pharmacogenomic testing becomes more sophisticated, it will be possible to abandon “trial and error” strategies and begin to provide individualized care utilizing metabolic and receptor pharmacogenomics. Using composite data, clinicians will have an unprecedented degree of molecular information available to help them choose effective medication-based treatments while minimizing the potential for ADEs.


As clinicians continue to treat pediatric patients with psychotropics, every relevant clinical observation and laboratory assessment should be considered to increase the likelihood of achieving remission of symptoms with minimal ADEs. Reviewing the results of pharmacogenomic testing prior to writing an initial prescription now provides clinicians useful individualized data that can be reviewed with the patient and family to inform them about the role that metabolism may play in treatment response as well as the possibility of ADEs. It is the authors’ belief that pharmacogenomic testing has a significant role in modern psychopharmacologic practice and that the associated expenses are already outweighed by the potential benefits of more individualized prescriptions.  PP



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67.    Volavka J, Czobor P, Cooper TB, et al. Prolactin levels in schizophrenia and schizoaffective disorder patients treated with clozapine, olanzapine, risperidone, or haloperidol. J Clin Psychiatry. 2004;65(1):57-61.
68.    Dahl ML. Cytochrome P450 phenotyping/genotyping in patients receiving antipsychotics: useful aid to prescribing? Clin Pharmacokinet. 2002;41(7):453-470.
69.    Bertilsson L, Dahl ML, Sjöqvist F, et al. Molecular basis for rational megaprescribing in ultrarapid hydroxylators of debrisoquine. Lancet. 1993;341(8836):63.
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71.    Pottier N, Cheok M, Kager L. Antileukemic drug effects in childhood acute lymphoblastic leukemia. Expert Rev Clin Pharmacol. 2008;1(3):401-413.
72.    Ansari M, Krajinovic M. Pharmacogenomics in cancer treatment defining genetic bases for inter-individual differences in responses to chemotherapy. Curr Opin Pediatr. 2007;19(1):15-22.
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74.    Cheok MH, Evans WE. Acute lymphoblastic leukaemia: A model for the pharmacogenomics of cancer therapy. Nat Rev Cancer. 2006;6(2):117-129.
75.    Brenner TL, Pui CH, Evans WE. Pharmacogenomics of childhood acute lymphoblastic leukemia. Curr Opin Mol Ther. 2001;3(6):567-578.
76.    Rogers AJ, Tantisira KG, Fuhlbrigge AL, et al. Predictors of poor response during asthma therapy differ with definition of outcome. Pharmacogenomics. 2009;10(8):1231-1242.
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Dr. Kung is assistant professor of psychiatry and consultant in psychiatry, and Dr. Li is psychiatry resident, both in the Department of Psychiatry and Psychology at the Mayo Clinic in Rochester, Minnesota.

Disclosures: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Simon Kung, MD, Mayo Clinic, 200 First St SW, Rochester, MN 55905; Tel: 507-255-7184; Fax: 507-284-3933; E-mail: kung.simon@mayo.edu.


Pharmacogenomic testing is clinically available to assist with medication selection in treatment-resistant depression (TRD). Common tests include the cytochrome P450 (CYP) 2D6 and 2C19 enzymes, the serotonin transporter gene, and the serotonin receptor gene. There are practical recommendations of interventions which can be supported from the literature. Identification of a CYP2D6 poor metabolizer would result in recommending a lower dosage of medications metabolized by CYP2D6, or avoiding the use of CYP2D6 medications. Identification of a serotonin transporter gene short/short genotype suggests more adverse effects, less response, or longer time to respond to selective serotonin reuptake inhibitors (SSRIs), and may warrant focusing treatment with non-SSRIs. Numerous other genotypes have been studied but with mixed implications. The use of pharmacogenomic testing can help the clinician rationalize medication selection and reduce the numerous medication combinations used in TRD. Further research and clinical experience will continue to define the clinical utility of this testing.

Focus Points

• Pharmacogenomic testing can be clinically used in guiding medication selection for treatment-resistant depression.
• Cytochrome P450 metabolizer status can guide whether the clinician uses medications metabolized by a specific pathway or uses different dosing ranges.
• The serotonin transporter gene short/short genotype has been associated with adverse reactions and less response to selective serotonin reuptake inhibitors (SSRIs), thus clinicians might choose a non-SSRI for such patients.
• Further research and clinical practice will help define the utility of pharmacogenomic testing.



Treatment-resistant depression (TRD) is a common occurrence in clinical practice. Depending on the operational definitions, studied populations and analytic methods used, prevalence ranges from 15% to 80%.1 Results from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study suggest that ~50% of “real world” patients with psychiatric and medical comorbidity who meet criteria for major depressive disorder (MDD) fail to achieve remission, even after four carefully monitored sequenced treatments.2

The most commonly adopted definition of TRD evolved from >15 historic definitions is “major depression with poor response to two adequate trials with different classes of antidepressants, given in an adequate dose for sufficient time.”3 Staging models of TRD reflect the severity of treatment resistance, factoring in the number of failed trials and intensity or optimization of each trial.4

Numerous strategies are used in TRD, including psychotherapy, pharmacotherapy using augmentation strategies, and brain stimulation techniques such as transcranial magnetic stimulation, vagus nerve stimulation, and electroconvulsive therapy. Deep brain stimulation and magnetic seizure therapy are investigational treatments.5 However, the most common treatment for TRD is the selection of alternative antidepressant trials. Algorithms have been developed to guide pharmacotherapy.6

Given the trial-and-error nature of medication treatment for TRD, a method which could decrease the number of trials needed to achieve remission would be valuable. There has been much research into the use of genotyping to predict drug metabolism (pharmacokinetic) and genotyping to determine serotonin gene variants (pharmacodynamic) associated with drug response. Both strategies provide information that can increase the likelihood that a medication trial will be helpful.

This article reviews our current knowledge of pharmacogenomic testing designed to predict antidepressant adverse effects and response. Clinical implications for the care of patients with MDD and TRD are discussed.



Cytochrome P450 (CYP) enzymes are involved with the metabolism of most medications, including antidepressants. Some medications, such as codeine and tamoxifen, are pro-drugs which require activation by CYP enzyme. Several CYP isoenzymes are involved with antidepressant metabolism, mainly the 2D6 and 2C19, and to a lesser extent, 2C9 and 1A2.7 Polymorphisms in the genes that code for these enzymes result in varying drug levels in an individual. The phenotypes typically range from a “poor” metabolizer (PM) with little or no enzyme activity, to an “intermediate” metabolizer with less than normal activity, to the “extensive” normal type, and to the “ultra-rapid” metabolizer (UM) with greatly increased activity. In patients of European ancestry, the distribution for CYP2D6 is ~10% PMs and 2% to 3% UMs. The phenotype frequencies for patients of European ancestry for CYP2C19 are ~3% PMs and 4% UMs. Drug metabolizing enzyme gene polymorphisms play a role in the interethnic variations in drug metabolism given that up to 20% of patients of Asian ancestry are CYP2C19 PMs.8 Generally, poor metabolizers experience more side effects and ultra-rapid metabolizers are less likely to respond to treatment with an antidepressant that is a substrate of the enzyme.

A clinical laboratory test for CYP2D6 genotyping has been available since 2003. Subsequently, clinical laboratory tests for CYP enzymes 2C19, 2C9, and 1A2 have become available. CYP 3A4 is an important enzyme involved in medication metabolism as well, but does not have many polymorphisms of functional significance.9

A current problem is that there is not a single standard for predicting the phenotype based on genotype. Consequently, different laboratories provide differing phenotype interpretations for the same genotype. This problem is compounded because different laboratories analyze for different sets of alleles. Another less problematic issue is that new alleles continue to be identified.10


Associations with Plasma Concentrations, Adverse Effects, and Treatment Response

The consequence of the CYP genotype on the pharmacokinetics of many antidepressants has been demonstrated. Desipramine,11 venlafaxine,12,13 nortriptyline,14 doxepin,15 imipramine,16 paroxetine,17 fluvoxamine,18 fluoxetine and paroxetine,19 and amitriptyline and nortriptyline20 have significant correlations between CYP2D6 genotypes and their plasma concentrations. However, the implications of these variable serum concentrations are not completely correlated with side effects or therapeutic response.11,13,21-23

CYP2C19 genotypes have been associated with metabolism of imipramine,24 sertraline,25,26 citalopram/escitalopram,27 and clomipramine.28 A study combining genotypes 2D6, 2C19, and 2C9 found significant influence of the 2D6 genotype, minor influence of the 2C19 genotype, and no influence of the 2C9 genotype on plasma concentrations of citalopram, paroxetine, fluvoxamine, and sertraline.29

Many studies show that poor and intermediate 2D6 metabolizers have been associated with more adverse effects to CYP2D6-dependent antidepressants.30-35 However, in some reports the risk for adverse effects have not reached statistical significance.13,36-38 These negative studies have had issues related to comprehensiveness of genotyping and sample size.

There are mixed reports of CYP2D6 genotyping associations with antidepressant response. UMs have been associated with non-response to antidepressants in several studies.17,31,39 However, in a retrospective study40 of 81 responders and 197 non-responders, CYP2D6 metabolizer status was not associated with either response or remission rates.


Practical Recommendations

Pharmacokinetic genotyping provides probabilistic estimates of side effects and efficacy in patients with PM and UM phenotypes. Its usefulness includes guiding certain antidepressant dosage and understanding and avoiding drug-drug interactions (DDIs), especially when 34% of patients in a primary care setting are on an antidepressant and ≥3 medications.41 The current standard clinical practice in using tricyclic antidepressants (TCAs) is to dose until reaching a pre-determined “therapeutic” serum drug level. For newer antidepressants, clinicians sometimes titrate the dose until a patient experiences benefit or uncomfortable side effects. Consequently, patients can be placed on dosages exceeding the manufacturer’s recommended usual dosages. The determination that a patient is an ultra-rapid metabolizer provides a rationale for a patient’s capacity to tolerate higher than recommended doses. Conversely, clinicians should be more cautious with substrate medications if a patient is not able to produce sufficient active enzyme necessary for the metabolism of the drug.

Pharmacokinetic reviews have suggested decreasing by ~50% the dosages of TCAs and risperidone in patients who are CYP2D6 PM, and using higher dosages of a TCA in UM.42-45 More specific dose adjustments have been proposed for the antidepressants imipramine, desipramine, nortriptyline, clomipramine, paroxetine, venlafaxine, amitriptyline, buproprion, citalopram, sertraline, and fluvoxamine, as well as the antipsychotics perphenazine, thioridazine, olanzapine, aripiprazole, haloperidol, and risperidone.44 Another review41 estimates the potential for antidepressants to be the perpetrator of a DDI mediated by effects on CYP2D6 enzymes as substantial (>150%) for paroxetine and fluoxetine; moderate (50% to 150%) for duloxetine; and mild (20% to 50%) for venlafaxine, sertraline, citalopram, and escitalopram.

Fortunately, for the newer antidepressants, clinically significant drug interactions from CYP inhibition are less frequent.46 Psychotropic medications which are not metabolized by CYP2D6 have been developed (eg, desvenlafaxine).

There is one psychotropic medication for which the Food and Drug Administration has made a firm recommendation for genetic testing (HLA-B*1502). Carbamazepine in patients with Asian ancestry with this variant have been shown to be at increased risk of life-threatening skin reactions such as Stevens-Johnson syndrome.47



In addition to CYP enzyme genes, several genes in the serotonin pathway have been studied for their potential role in the susceptibility to depression, adverse effects, and treatment response to psychotropic medications. Commonly studied genes include the 5-HTTLPR promoter region of the serotonin transporter gene (SLC6A4) and the serotonin receptor gene subtypes 5-HT2A and 5-HT2C.


Adverse Effects of Psychotropic Medications

Several studies reported that 5-HTTLPR L alleles are associated with fewer selective serotonin reuptake inhibitor (SSRI) side effects.48 In a study49 comparing the SSRI paroxetine versus the non-SSRI mirtazapine, patients with 5-HTTLPR S alleles had worse side effects with paroxetine but tolerated mirtazapine better. A possible interaction of 5-HTTLPR L allele and oral contraceptives associated with sexual side effects has also been reported.50 5-HTTLPR S alleles have also been associated with antidepressant-induced mania.51

The serotonin receptor genes 5-HT2A and 5-HT2C have also been associated with psychotropic adverse effects. Paroxetine side-effect severity and discontinuation was associated with the number of 5-HT2A C alleles.38 Various 5-HT2A polymorphisms have also been associated with fewer SSRI side effects including gastrointestinal side effects52 or increased side effects such as sexual side effects.53 An 5-HT2C polymorphism was reported to be protective against significant antipsychotic-induced weight gain54 and associated with tardive dyskinesia, although the association was not significant.55


Response to Treatment

A 2007 meta-analysis of 5-HTTLPR and SSRI treatment reported that the L allele is associated with a better response independent of ethnic differences, and patients with the S/S genotype take >4 weeks to respond and have difficulties reaching remission.56 While there is conflicting data related to the effects of SLC6A4 in patients of African-American or Hispanic ancestry,57,58 an analysis of STAR*D patients restricted to the white non-Hispanic subgroup confirmed an association of SLC6A4 activity level and remission with citalopram.59

Ethnic and gender differences can be seen in various reports. A 2009 study60 of Mexican Americans reported a SLC6A4 haplotype associated with remission using desipramine or fluoxetine. Korean patients with the SLC6A4 S/S genotype responded better to mirtazapine compared to those with the L/L or L/S genotype.61 Chinese patients with the L/L genotype experienced better clinical response to SSRIs compared to serotonin norepinephrine reuptake inhibitors.62 Regarding gender, in women with the SLC6A4 S/S genotype, lower efficacy was reported for SSRIs as well as non-SSRIs.63,64

Other reports of SLC6A4 associations with antidepressant response are interesting. In geriatric patients, SLC6A4 was reported to interact with serum paroxetine levels to influence antidepressant response.65 In a positron emission tomography imaging study, higher serotonin transporter occupancy was associated with clinical improvement with paroxetine in patients with L/L.66 In patients with S/S genotype, antidepressant augmentation with pindolol and lithium was associated with better response.67,68

For 5-HT2A, meta-analysis of antidepressant treatment response showed a contribution to better response with a specific polymorphism, particularly in Asians.52 In the STAR*D data,69 participants who were homozygous for the 5-HT2A A allele of a newly identified variant (rs7997012) had an 18% reduction in absolute risk of having no response to treatment, compared with those homozygous for the other allele. The A allele was over six times more frequent in white than in black participants, and treatment was less effective among black participants.


Practical Recommendations

Pharmacodynamic reviews of SLC6A4 suggest that patients with the S/S genotype do not respond as well to SSRI antidepressants, and may experience more side effects.48,52,70 Thus, a practical approach is to use a non-SSRI in a patient who is SLC6A4 S/S or S/L. A decision analytic model of pre-treatment testing for SLC6A4 concluded that such testing would result in more patients experiencing remission earlier in treatment.71

Knowledge of 5-HT2A alleles might suggest the clinician try citalopram, or if generalization is possible, an SSRI, in patients who are homozygous for the 5-HT2A A allele.69 If a clinician is making a decision whether to augment an antidepressant with an antipsychotic, results of the 5-HT2C might not support an antipsychotic if the patient has the allele associated with increased weight gain with antipsychotics.


Pharmacogenomics in the Perspective of TRD

TRD represents a major public health concern, since it is associated with higher rates of relapse, poorer quality of life, deleterious personal and societal economic ramifications, and increased mortality rates.72,73 In the biopsychosocial model of depression treatment, the biologic standard of care is the medication trial. Numerous algorithms are available for guidance.6,74 Using the example of the Texas Medication Algorithm Project (TMAP), given that each adequate medication trial is ~2 months, and if a patient tries at least 3 SSRIs and 3 non-SSRIs, that would already be 1 year of medication trials. For each antidepressant, augmenting with two different medications such as a mood stabilizer or an antipsychotic for each of the antidepressants tried increases each medication trial by a few more months, and one can appreciate how patients might go through 4 or 5 years of medication trials. By incorporating genotyping results into an algorithm such as TMAP, one should be able to reduce the number of medication trials needed.

Genotyping can also explain some of the adverse events associated with medications. Consider the case example of a 58-year-old Caucasian woman with depression who has not responded to citalopram and bupropion. The clinician selects nortriptyline as the next medication trial, and titrates to a therapeutic dose based on serum level. As her depression is not improving, the clinician adds fluoxetine, noting that the combination of an SSRI and a TCA is listed in Stage 3 of the TMAP. Two weeks later, the patient experiences lethargy and unsteadiness, to the point of falling and sustaining a wrist fracture. A nortriptyline serum level shows it is now in the toxic range, and both medications are held. Two weeks later, the patient returns to her baseline state. Genotyping is obtained, and reveals that the patient is an intermediate metabolizer of CYP2D6. The explanation in this situation is that nortriptyline and fluoxetine are both metabolized by CYP2D6, and additionally, fluoxetine is a strong inhibitor of 2D6. The patient was already an intermediate metabolizer, and by inhibiting that state, effectively converted the patient to a poor metabolizer, which resulted in the nortriptyline toxicity and side effects. Adverse effects are common reasons for switching antidepressants, which leads to more medication trials and a sense of medication “resistance.” Understanding and predicting adverse effects can improve the patient’s experience and compliance with medications, leading to a better outcome.

A patient’s genetic makeup is only one of the many complex factors involved in his or her response to antidepressants. Other factors include diet, caffeine, nicotine, age, medical illness, and concurrent medications. In addition, appropriate attention should be given to the psychological and social stresses aspects of the patients’ illness. Psychotherapies such as cognitive behavioral therapy and acceptance and commitment therapy can be helpful.75,76 Patients with aversive social contexts for their depression also have consistently lower remission rates, indicating the need for social interventions.77



Depression can be difficult to treat, especially with its biopsychosocial contributors. From the biologic perspective, clinicians rely on medication trials which might span several years because of the large number of antidepressants available and the various augmentation strategies. Patients understandably become frustrated with such treatment techniques and look towards methods which might help them identify the optimal medication or combination to treat their depression.

There has been much research into whether pharmacogenomic testing might provide sufficient clinical information to guide psychotropic medication choices and thus decrease the trial and error approach of medication management. With regards to pharmacokinetic testing, specifically CYP2D6 and CYP2C19, identifying poor metabolizers in order to help with medication selection and dosage adjustments can be helpful. In patients presenting with numerous side effects, it can also confirm whether a patient is experiencing side effects because of metabolizer status. From the pharmacodynamic perspective, many genes have been studied, with the most common being the serotonin transporter and serotonin receptor genes. Patients of European ancestry with a serotonin transporter gene S/S or S/L genotype seem to not tolerate or not respond as well to SSRIs compared to patients with the L/L genotype. Various serotonin receptor gene alleles have also been associated with increased or decreased response to SSRIs as well as side effects.

The response of an individual to antidepressant treatment is not only influenced by the limited number of genes that are currently tested. Genome-wide association studies (GWAS) to investigate the entire genome without focus on a specific hypothesis and genomic area represent a new and promising methodologic strategy. A recent GWAS found remission associated with the number of predicted “response” alleles, and supported that antidepressant response emerges from a multitude of genetic variants.78,79 Further research is predicted to reveal additional clinical applications to guide treatment.  PP


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48.    Horstmann S, Binder EB. Pharmacogenomics of antidepressant drugs. Pharmacol Ther. 2009;124(1):57-73.
49.    Murphy GM Jr, Hollander SB, Rodrigues HE, Kremer C, Schatzberg AF. Effects of the serotonin transporter gene promoter polymorphism on mirtazapine and paroxetine efficacy and adverse events in geriatric major depression. Arch Gen Psychiatry. 2004;61(11):1163-1169.
50.    Bishop JR, Ellingrod VL, Akroush M, Moline J. The association of serotonin transporter genotypes and selective serotonin reuptake inhibitor (SSRI)-associated sexual side effects: possible relationship to oral contraceptives. Hum Psychopharmacol. 2009;24(3):207-215.
51.    Ferreira Ade A, Neves FS, da Rocha FF, et al. The role of 5-HTTLPR polymorphism in antidepressant-associated mania in bipolar disorder. J Affect Disord. 2009;112(1-3):267-272.
52.    Kato M, Serretti A. Review and meta-analysis of antidepressant pharmacogenetic findings in major depressive disorder. Mol Psychiatry. Nov 4, 2008. [Epub ahead of print].
53.    Bishop JR, Moline J, Ellingrod VL, Schultz SK, Clayton AH. Serotonin 2A -1438 G/A and G-protein Beta3 subunit C825T polymorphisms in patients with depression and SSRI-associated sexual side-effects. Neuropsychopharmacology. 2006;31(10):2281-2288.
54.    Reynolds GP, Zhang Z, Zhang X. Polymorphism of the promoter region of the serotonin 5-HT(2C) receptor gene and clozapine-induced weight gain. Am J Psychiatry. 2003;160(4):677-679.
55.    Reynolds GP, Templeman LA, Zhang ZJ. The role of 5-HT2C receptor polymorphisms in the pharmacogenetics of antipsychotic drug treatment. Prog Neuropsychopharmacol Biol Psychiatry. 2005;29(6):1021-1028.
56.    Serretti A, Kato M, De Ronchi D, Kinoshita T. Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with selective serotonin reuptake inhibitor efficacy in depressed patients. Mol Psychiatry. 2007;12(3):247-257.
57.    Kraft JB, Peters EJ, Slager SL, et al. Analysis of association between the serotonin transporter and antidepressant response in a large clinical sample. Biol Psychiatry. 2007;61(6):734-742.
58.    Hu XZ, Rush AJ, Charney D, et al. Association between a functional serotonin transporter promoter polymorphism and citalopram treatment in adult outpatients with major depression. Arch Gen Psychiatry. 2007;64(7):783-792.
59.    Mrazek DA, Rush AJ, Biernacka JM, et al. SLC6A4 variation and citalopram response. Am J Med Genet B Neuropsychiatr Genet. 2009;150B(3):341-351.
60.    Dong C, Wong ML, Licinio J. Sequence variations of ABCB1, SLC6A2, SLC6A3, SLC6A4, CREB1, CRHR1 and NTRK2: association with major depression and antidepressant response in Mexican-Americans. Mol Psychiatry. 2009;14(12):1105-1118.
61.    Kang RH, Wong ML, Choi MJ, Paik JW, Lee MS. Association study of the serotonin transporter promoter polymorphism and mirtazapine antidepressant response in major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31(6):1317-1321.
62.    Min W, Li T, Ma X, et al. Monoamine transporter gene polymorphisms affect susceptibility to depression and predict antidepressant response. Psychopharmacology (Berl). 2009;205(3):409-417.
63.    Smits KM, Smits LJ, Peeters FP, et al. The influence of 5-HTTLPR and STin2 polymorphisms in the serotonin transporter gene on treatment effect of selective serotonin reuptake inhibitors in depressive patients. Psychiatr Genet. 2008;18(4):184-190.
64.    Gressier F, Bouaziz E, Verstuyft C, Hardy P, Becquemont L, Corruble E. 5-HTTLPR modulates antidepressant efficacy in depressed women. Psychiatr Genet. 2009;19(4):195-200.
65.    Lotrich FE, Pollock BG, Kirshner M, Ferrell RF, Reynolds Iii CF. Serotonin transporter genotype interacts with paroxetine plasma levels to influence depression treatment response in geriatric patients. J Psychiatry Neurosci. 2008;33(2):123-130.
66.    Ruhe HG, Ooteman W, Booij J, et al. Serotonin transporter gene promoter polymorphisms modify the association between paroxetine serotonin transporter occupancy and clinical response in major depressive disorder. Pharmacogenet Genomics. 2009;19(1):67-76.
67.    Zanardi R, Serretti A, Rossini D, et al. Factors affecting fluvoxamine antidepressant activity: influence of pindolol and 5-HTTLPR in delusional and nondelusional depression. Biol Psychiatry. 2001;50(5):323-330.
68.    Stamm TJ, Adli M, Kirchheiner J, et al. Serotonin transporter gene and response to lithium augmentation in depression. Psychiatr Genet. 2008;18(2):92-97.
69.    McMahon FJ, Buervenich S, Charney D, et al. Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am J Hum Genet. 2006;78(5):804-814.
70.    Luddington NS, Mandadapu A, Husk M, El-Mallakh RS. Clinical implications of genetic variation in the serotonin transporter promoter region: a review. Prim Care Companion J Clin Psychiatry. 2009;11(3):93-102.
71.    Smits KM, Smits LJ, Schouten JS, Peeters FP, Prins MH. Does pretreatment testing for serotonin transporter polymorphisms lead to earlier effects of drug treatment in patients with major depression? A decision-analytic model. Clin Ther. 2007;29(4):691-702.
72.    Greden JF. The burden of disease for treatment-resistant depression. J Clin Psychiatry. 2001;62 suppl 16:26-31.
73.    Fekadu A, Wooderson SC, Markopoulo K, Donaldson C, Papadopoulos A, Cleare AJ. What happens to patients with treatment-resistant depression? A systematic review of medium to long term outcome studies. J Affect Disord. 2009;116(1-2):4-11.
74.    TMAP. Texas Medication Algorithm Project. Available at: www.dshs.state.tx.us/mhprograms/disclaimer.shtm. Accessed February 11, 2010.
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76.    Pull CB. Current empirical status of acceptance and commitment therapy. Curr Opin Psychiatry. 2009;22(1):55-60.
77.    Brown GW, Harris TO, Kendrick T, et al. Antidepressants, social adversity and outcome of depression in general practice. J Affect Disord. 2010;121(3):239-246.
78.    Sabbagh A, Darlu P. Data-mining methods as useful tools for predicting individual drug response: application to CYP2D6 data. Hum Hered. 2006;62(3):119-134.
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Dr. Weiss is head of the Provincial ADHD Program and clinical professor at the University of British Columbia Children’s and Women’s Health Centre in Vancouver.

Disclosure: Dr. Weiss is a consultant to and receives grant support from Eli Lilly, Janssen, Purdue, and Shire. She also receives grant support from the Canadian Institutes of Health Research.

Please direct all correspondence to: Margaret D Weiss MD PhD, Head, Provincial ADHD Program, Clinical Professor, University of British Columbia, Children’s and Women’s Health Centre, Box 178 , 4500 Oak St, Vancouver, BC V7T 2Y2; Tel: 604-875-2010; Fax: 604-875-2099; E-mail: mweiss@cw.bc.ca.


All assessments in child psychiatry involve evaluation of particular areas that are not typical in an adult assessment. These include a detailed school history, developmental history, a family interview, and collateral information obtained usually by rating scales from teachers and parents. In certain aspects of adult psychiatry some of these child procedures may also serve to augment the assessment process. Collateral information may be useful in assessment of a patient without insight, such as a patient with hypomania. Rating scales can be useful in identification of severity and follow up of improvement. Broad-based rating scales can be used to assure identification of diagnoses that might be missed by the clinician, or that the patient is reluctant to discuss.

Just as there are procedures that are unique to child psychiatry that may be of benefit to adult psychiatry, there are procedures unique to assessment of attention-deficit/hyperactivity disorder (ADHD) for patients of all ages that may be useful to general child or adult psychiatrists. I will identify the modifications to the assessment process now in place in our Provincial ADHD Program which I think may be of use to those in general practice seeing patients with ADHD, or even to practitioners who are seeing patients with other diagnoses where the same type of issues arise.

In order to improve the efficiency of the assessment process and optimize the time available for discussion of psychosocial care we need to know quickly and as easily as possible Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition1 diagnoses that might have been missed, are comorbid, or represent differential diagnoses. We also need to identify those diagnoses that are apparent to different observers and in different settings. The Kiddie-Schedule for Affective Disorders and Schizophrenia (KSADS) has been used clinically for diagnoses, but the reality of the constrictions on the clinical time we have available is that this is expensive and limited to information from the family. The KSADS and other diagnostic interviews were designed for research. However, the objective of such interviews is as germane in practice as in research. For this reason, the Canadian ADHD Resource Alliance2 has developed a DSM-IV checklist that is completed by the patient and a collateral informant prior to interview. The advantage of this interview is not a substitute to the mental status, but to serve as a guide to the mental status and to assure the clinician remembers what the DSM criteria are as well as to identify important patient/collateral differences.

Since the emergence of the DSM, the diagnostic process has focused heavily on symptoms, and diagnostic criteria. However, patients do not typically present with the chief complaint that they have a DSM disorder. More often, they present with a problem in life functioning where they have difficulty meeting the new expectations of a developmental transition. While Axis V is meant to identify impairment, there is no description of what impairment is—whether it represents absolute impairment or impairment relative to potential—or the settings in which such impairment occurs. Nor on Axis V is there anything like the diagnostic criteria that bring interrater reliability and definition to Axis I.

The reality familiar to all clinicians is that there are patients who have significant diagnoses and function well and patients who have a vague mixture of symptoms from different diagnoses who are severely impaired. For this purpose, prior and post interview from the Weiss Functional Impairment Rating Scale for Self (WFIRS-S: adolescents or adults; Table 1) or WFIR for Parents (Table 2) examines impairment in each of the major domains. Like the Symptom Record, this can be reviewed, discussed with the patient, and used as a cross check on the interview. Within the busy service requirements of the ADHD clinic, psychiatrists do not have the luxury of psychologists to score complex scales. We use the simple rule of rating both symptoms and functional items that are of clinical significance by simply counting those items rated as 2 (pretty much) or 3 (very much) by the patient or informant. While simple, this is much like the Clinical Global Impression–Severity scale in that it gives a precise and clear characterization of the patient’s difficulties.




Some differentials that are more common in ADHD, and therefore a necessary part of the evaluation. However, while they may be more common, they are by no means unique to ADHD. An ADHD assessment requires an evaluation for learning disabilities, sleep, nutrition, bullying, family discipline, and parental frustration. as well as capacity for activities of daily living, school or work success and adaptations, and risk factors such as drug use, driving, or injuries. Evaluation of these differentials and risk factors by self and other report on the Symptom Record and the WFIRS assures that patients receive the clinical attention they deserve.

Perhaps the most important and most often missed aspect of psychiatric assessment is that we are trained to be pathology sensitive. However, from the patient’s point of view identification and reinforcement of strengths and successes sets a tone and models a positive experience. We know very little about what determines long-term outcome apart from obvious advantages such as income, personality, family support, and resilience. However, one aspect of possible prognostic signficance that is likely to be stable over time is the capacity to be compassionate and kind. For example, one of the most widely used child broadband rating scales in the public domain that is age and gender normed, the Strengths and Difficulties Questionnaire,3 has as one of its five subscales “prosocial skills.” Kindness may well be a stable characteristic that when assessed at any age represents a relative strength that can be drawn on to identify to the patient that whatever the symptomatology, her or she is “a good person.” Outcome is not only determined by what is disturbed, but also by what the patient does well. Are they empathic? Do they have a special passion for a skill they do well? Are they psychologically minded?

Apart from inclusion of the whole family, one aspect of child psychiatry that is unique and critical to ADHD is the developmental history. Has their been in utero exposure to nicotine, alcohol, or other drugs? Was their compromise to the newborn during delivery? What was the child’s early temperament? (Temperament tends to be relatively stable, and early memories are of interest.) Were there notable developmental delays, such as clumsiness, indicative of residual developmental coordination disorder? An assessment of ADHD in adults requires the same type of evaluation, since like all neuropsychiatric conditions grown up, early childhood history is critical to establishing a developmental onset of difficulty. Again, while these questions are critical to assessment of ADHD, they may identify early onset prognostic deficits relevant to all adult conditions.

When one asks a child if they have problems paying attention or whether they get into trouble, they often know the answer. When asked if the problem is small, medium, or large, their assessment is also not unlikely to match the results of systematic interview. The point is simple: in adult psychiatry we have the advantage that we interview the patient directly, but nonetheless we may fail to bring into the office those significant others who know the patient in a way he cannot know him or herself. In child psychiatry, we often focus our interview on parent and teacher information. However, the informant who remains critical to an ADHD assessment or any child assessment is the child. A child might say, “I am lazy.” “I only like recess because it is the only part of school that is not boring.” “I have no friends because I am bad.” Assuring that the child remains an important part of the interview provides clues to diagnosis, child insight, and functional impairment. It also tells the clinician the child’s own experience of the impact of his or her disorder on quality of life. Whether this is an assessment of an adult with ADHD and we decide to include the spouse, or an assessment of the child and we interview the caregivers and obtain information from the school, assessment of ADHD is a reminder to all psychiatry that collateral information often brings surprises. In adult psychiatry, where most patients are seen individually for 1 hour, the use of collateral scales has a major role to play that has been under utilized.

The Symptom Record completed by patient and collateral provides a simple, cost effective way to obtain a pathway into the key problems, and an assurance that we won’t miss disorders such as learning problems, sleep, or tics that might otherwise be missed. The Weiss Functional Impairment Rating Scales reminds us that patients came to the interview hoping to be able to do things or meet developmental milestones that have remained closed to them. It reminds the patient and the doctor that even when we get the diagnosis right, if we do not know the problem, the patient will not significantly progress.

ADHD is a neurodevelopmental condition which like many mental health disorders carries through the life cycle, presenting new difficulties as the patient faces new challenges. What we have to learn from assessment of ADHD in adults and children is that a developmental history, collateral information, and assessment of developmental cormorbidities such as sleep or learning have the possibility to deepen and create a better understanding for patients of all ages and all disorders.  PP




1.    Diagnostic and Statistical Manual of Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.
2.    CADDRA. The Canadian Attention Deficit Hyperactivity Disorder Resource Alliance. Available at: www.caddra.ca. Accessed April 12, 2010.
3.    SDQ. Information for researchers and professionals about the Strengths & Difficulties Questionnaires. Available at: www.sdqinfo.com. Accessed April 12, 2010.


Dr. Kennedy is professor in the Department of Psychiatry and Behavioral Sciences at Albert Einstein College of Medicine, and director of the Division of Geriatric Psychiatry at Montefiore Medical Center in the Bronx, New York.

Disclosure: Dr. Kennedy reports no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Gary J. Kennedy, MD, Director, Department of Geriatric Psychiatry, MMC, 111 East 210th St, Klau One, Bronx, NY 10467; Tel: 718-920-4236; Fax: 718-920-6538; E-mail: gjkennedy@msn.com.


The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition,1 is scheduled for release in May 2013. In February 2010, the preliminary draft revisions to the current diagnostic criteria became available for review and comment. Although diagnostic biomarkers and neuropsychologic criteria for dementia have yet to emerge, there are conceptual advances evident in the proposed criteria which have substantial implications for treatment. What follows is a discussion of the proposed revisions to help readers who may want to submit comments during the review period.

The DSM-5 proposes four major changes2 for the cognitive disorders listed in the DSM-IV-TR 3 as delirium, dementia, and amnestic disorders. These include dropping the term “dementia” entirely, adding a new diagnostic category titled “minor neurocognitive disorder,” and explicitly categorizing the syndromes of psychosis and depression previously described for Alzheimer’s disease but not mentioned in the DSM-IV. 4 The fourth change is the provision of far greater detail, examples, and assessment techniques for the specific cognitive domains of impairment. Each change reflects advances in neuroscience, neuropsychology, and neuroimaging. However, the first three are also the result of a conceptual process that began more than a century ago.


Historic Background

Kraepelin assigned the name “Alzheimer’s disease” to Alzheimer’s initial case reports of marked cognitive deterioration associated with neurofibrillary tangles in 1907 and amyloid plaques in 1911.5 But “Alzheimer’s disease” does not appear in the DSM until the DSM-III.6 Controversy arose over whether Alzheimer’s findings were those of a genuine disease or of normal aging. In addition, there was no consensus about how to classify the illness if it indeed was a disease. In 1951, the United States Public Health Service established a work group to address difficulties perceived in the International Classification of Diseases, Sixth Edition (ICD-6).7 Among the shortcomings were ICD-6’s failure to include chronic brain syndromes (dementias) within the coding rubric of mental disorders along with neurotic and behavioral reactions such as anxiety and depression. This was incongruent with the DSM-I,8 which was published in 1952. In addition, many of the “psychoses associated with organic factors,” meaning dementias, were lumped into a category labeled “psychoses with other demonstrable etiology.”9

Debates about the terminology of cognitive disorders continued through the publication of the DSM-II 10 and the ICD-8.11 Terms such as “brain syndrome” as well as “organic psychoses” and various modifiers were proposed. The term “psychosis” was used to denote severity rather than the presence of hallucinations or delusions. What current practitioners might refer to as vascular dementia would have been classified in the DSM-II as “psychoses associated with organic brain syndromes with cerebral arteriosclerosis (293.0) or other cerebrovascular disturbance (293.1). “Psychoses not attributed to physical conditions” included schizophrenia and manic depressive illness.10 Uncertainty about where to place these conditions and how to describe them reflects their dual identities as both neurologic and psychiatric disorders. This duality is also reflected in the functional versus organic terminology now thought to be out of date as well as inaccurate. Captioning neurodegenerative disorders in which mental rather than motor or perceptual deficits predominate is a historic trend across the DSMs. By transforming the cognitive disorders of the DSM-IV into neurocognitive disorders, the DSM-5 acknowledges the neurologic aspect of the illness without ceding the diagnosis entirely to neurology or primary care. The dementias are mental disorders. Nonetheless, some states bar people with a diagnosis of dementia from receiving services at Medicaid-certified mental health clinics unless there is a specific diagnostic modifier denoting “depression” of “delusions,” or a concurrent major mental disorder such as major depressive disorder (MDD).12


Out with the Old, in with the New

Delirium, dementia, amnestic, and other cognitive disorders are subsumed in the DSM-5 under the category of “neurocognitive disorders.” Neurocognitive disorders, in contrast to neurodevelopmental disorders, are acquired and degenerative rather than inborn and apparent in childhood. The term was chosen in part to avoid the stigma associated with dementia when categorizing deficits among younger people with progressive cognitive decline associated with HIV or traumatic brain injury. Neurocognitive disorders are further divided into major and minor. The DSM-IV condition described as “age-related cognitive decline (ARCD)” appearing in “other conditions that may be a focus of clinical attention” would now appear under minor neurocognitive disorder in the DSM-5. This is a decided advance. Terms such as ARCD, cognitive impairment not dementia (CIND), mild cognitive impairment (MCI), amnestic MCI, and non-amnestic MCI—which have variable criteria but are often considered a prodrome of dementia—would now be listed as a minor neurocognitive disorder. More importantly, in contrast to those without detectable impairment, people with CIND exhibit both a greater prevalence of neuropsyschiatric symptoms such as depression as well as functional limitations.13

Minor neurocognitive disorder is analogous to minor depressive disorder, which appears in Appendix B of the DSM-IV along with subsyndromal depressive condition not elsewhere classified (CNEC). Indeed, subsyndromal depressive CNEC is further divided into prodromal depression and subsyndromal, and mixed subsyndromal anxiety-depressive disorder depending on duration, severity, or associated features, respectively. Both MCI and minor depression are similar in that they predict progression to either dementia or MDD. However, many people considered to have MCI or minor depression never develop a major mental illness. The certainty with which we can distinguish a symptom or performance profile which represents a genuine prodrome from periodic variability in cognitive performance or mood remains problematic. Nonetheless, identifying minor neurocognitive disorder as a DSM diagnosis reflects a growing consensus that MCI and CIND are too often the early manifestations of dementia. Additionally, not to have a “minor” diagnostic category would leave investigators and the public with the confusing terminology that followed in the wake of the DSM-IV.


Behavioral Disturbances Categorized

Behavioral disturbances of Alzheimer’s disease are prevalent and add excess disability for the patient and distress for caregivers. Community-based studies13-15 find agitation, apathy, depressed mood, delusions, and less frequently hallucinations to be the most common problems. In the DSM-II, the dementias were categorized as either psychotic or non-psychotic organic brain syndromes. Severity of impairment—not the presence of delusions or hallucinations—determined whether or not the disorder was of psychotic proportions. Hallucinations, delusions, and alterations in mood were considered part of the disorder but no modifying code or category was proposed. With the publication of the DSM-IV-TR, modifying codes had been added to reflect the presence or absence of behavioral disturbance.3 For vascular but not Alzheimer’s dementia, modifying codes included “with delirium,” “with delusions,” and “with depressed mood.” Two syndromes are proposed for the DSM-5,  but specifically for Alzheimer’s disease. The first is a depressive syndrome in which three symptoms of MDD must be present for a minimum of 2 weeks and cause disability or distress. The second is a syndrome of psychosis in which delusions or hallucinations have been present at least intermittently for a minimum of 1 month and cause disability or distress. Alternatively, other behavioral problems such as agitation, aggression, apathy, wandering, disinhibition, or circadian rhythm disturbance might be coded as a fifth digit across any of the neurocognitive disorders. However, with behavioral problems so prevalent and so distressing to caregivers, the work group is wise to flag these matters as requiring additional input. Behavioral disturbance modifiers are necessary in some states for Medicaid-certified mental health clinics to provide services to people with dementia.12

Cognitive Domains Mature

The DSM-IV identifies impairments in memory and learning plus one of the following—aphasia, apraxia, agnosia, or executive dysfunction—as criteria for dementia. Deficits must cause social disability to justify the diagnosis. The proposal for the DSM-5 includes domains for “complex attention, executive ability, learning and memory, language, visuoconstructional-perceptual ability, and social cognition.” Each item has a paragraph describing major and minor deficits as well as definitions of the domain and examples of assessment procedures. Equally important are descriptions of how impairment within the domain disrupts behavior and threatens independence. The work group remains uncertain about how to formally portray domain-specific deficits. However, it seems critical to tailor the caregiver approach and structure the environment to take advantage of capacities which are preserved and to compensate for those which are deficient. Achieving the right fit between strengths and vulnerabilities would presumably lessen the patient’s disability, reduce the caregiver’s burden, and minimize the occurrence of behavioral disturbances. This is likely to be the case for people with Alzheimer’s, Parkinson’s, and Lewy Body diseases but may be equally important for veterans of Iraq and Afghanistan returning home with traumatic brain injury. Given the disappointing results from pharmacotherapy for the behavioral disturbances of dementia, a more exacting description of domain-specific deficits could be a major public health advance.16


Changes proposed in the DSM-5 related to delirium and dementia highlight the clinical nature of these diagnostic categories. Objective criteria from neuropsychological, imaging, or laboratory assessments are mentioned but neither specified nor required to make the diagnosis. This is a reflection more on the marked variation in neurobiology and cognitive performance between individuals both healthy and otherwise rather than a lack of reliable measures of change within the individual.13,16 The distinction between major and minor neurocognitive disorders also reflects the intense scientific interest in identifying the prodrome for dementia. Given the frequency with which MCI and CIND progress to dementia, failure to include minor neurocognitive disorder would seem a major error. However laudable it may be to avoid the stigma associated with the term “dementia,” substituting “neurocognitve disorder” reminds one of bipolar I (manic) and bipolar II (depressed) of the DSM-IV, which replaced the DSM-II’s “manic depressive illness.” Nonetheless, changes in nomenclature matter. Addition of salient behavioral problems to the diagnostic code regardless of etiology seems clinically sound. The adoption of modifiers to capture even one specific domain of cognitive deficits may lead to improved behavioral approaches. There is bound to be debate about “minor neurocognitive disorder” and the abandonment of “dementia” just as there has been for autism and Asperger’s syndrome.19 However, the clinical utility of noting behavioral disturbance and domain-specific deficits is hard to deny.  PP


1. Diagnostic and Statistical Manual for Mental Disorders. 5th ed. Washington, DC: American Psychiatric Association; In press.
2. Neurocognitive Disorders Work Group: Jeste D, Blacker D, Blazer D, et al. Draft dated 7 January 2010. Available at: http://www.dsm5.org/ProposedRevisions/Pages/Delirium,Dementia,Amnestic,OtherCognitive.aspx. Accessed April 9, 2010.
3. Diagnostic and Statistical Manual for Mental Disorders. 4th ed, text rev. Washington, DC: American Psychiatric Association; 2000.
4. Diagnostic and Statistical Manual for Mental Disorders. 4th ed. Washington, DC: American Psychiatric Association; 1994.
5. Diagnostic and Statistical Manual for Mental Disorders. 3rd ed. Washington, DC: American Psychiatric Association; 1980.
6. Graeber MB, Kösel S, Egensperger R, Banati RB, Müller U, Bise K, Hoff P, Möller HJ, Fujisawa K, Mehraein P. Rediscovery of the case described by Alois Alzheimer in 1911: historical, histological and molecular genetic analysis. Neurogenetics. 1997;1(1):73-80.
7. International Statistical Classification of Diseases and Related Health Problems. 6th rev. Geneva, Switzerland: World Health Organization; 1948.
8. Diagnostic and Statistical Manual for Mental Disorders. Washington, DC: American Psychiatric Association; 1952.
9. Kramer M. Introduction: the historical background of ICD-8. In: Diagnostic and Statistical Manual for Mental Disorders. 2nd ed. Washington, DC: American Psychiatric Association; 1968:xi-xv.
10. Diagnostic and Statistical Manual for Mental Disorders. 2nd ed. Washington, DC: American Psychiatric Association; 1968.
11. International Statistical Classification of Diseases and Related Health Problems. 8th rev. Geneva, Switzerland: World Health Organization; 1968.
12. Medicaid Requirements for OMH-Licensed Outpatient Programs. NYS Office of Mental Health. January 2004. Available at: www.omh.state.ny.us/omhweb/012104letter/medicaid.htm. Accessed April 16, 2010.
13. Okura T, Plassman BL, Steffens DC, Llewellyn DJ, Potter GG, Langa KM. Prevalence of neurospychiatic symptoms and their association with functional limitation in older adults in the United States: The Aging, Demographics, and Memory Study. J Am Geriatr Soc. 2010;58(2):330-337.
14. Lyketsos CG, Sheppard JM, Steinberg M, et al. Neuropsychiatric disturbance in Alzheimer’s disease clusters into three groups. Int J Geriatr Psychiatry. 2001;16(11):1043-1053.
15. Devanand DP, Jacobs DM, Tang MX, et al. The course of psychopathological features in mild to moderate Alzheimer’s disease. Arch Gen Psychiatry. 1997;54(3):257-263.
16. Holtzer R, Verghese J, Wang C, Hall CB, Lipton RB. Within-person across-neuropsychological test variability and incident dementia. JAMA. 2008;300(7):823-830.
17. Griffith HR, Stewart CC, Stoekel LE, et al. Magnetic resonance imaging volume of the angular gyri predicts financial skill deficits in people with amnestic mild cognitive impairment. J Am Geriatr Soc. 2010;58(2):265-274.
18. Kennedy GJ. From symptom palliation to disease modification: implications for dementia care. Primary Psychiatry. 2007;14(11):30-34.
19. Meiklejohn ST, Brehmer B, Chase I, Greenberg D. To the Editor. A separate label for Asperger’s. New York Times. February 15, 2010:A29.


Dr. Sussman is editor of Primary Psychiatry as well as Associate Dean for Post-Graduate Programs and professor of psychiatry at the New York University School of Medicine in New York City.

Dr. Sussman reports no affiliation with or financial interest in any organization that may pose a conflict of interest.

Email questions or comments to ns@mblcommunications.com


Selecting the best strategy to optimize antidepressant response is a major ongoing clinical challenge. The need for more effective approaches for producing remission has been made clear by recent evidence that confirms treatment with any single antidepressant drug produces remission in only ~33% of patients, and that when antidepressants do work, they are of most benefit to those with more severe depressive symptoms. Patients with moderate levels of depression who seek care because they are either distressed or impaired by their symptoms may, paradoxically, be more difficult to bring into remission than those with a more pronounced disorder. An abundance of studies have shown that numerous augmentation or switching strategies may be effective for some patients, but no body of evidence demonstrates consistent superiority of any. In summarizing lessons learned from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial, the most ambitious attempt to date to address the question of antidepressant enhancement options, Rush wrote that “the gap between what we do in practice and what we know is very large.”1 In the near future, another study should be published that looks at whether it is better to start treatment with a combination of antidepressants rather than monotherapy. In anticipation of that article, I want to review the STAR*D trial and its major finding and describe the Combining Medication to Enhance Depression Outcomes (CO-MED), which looks at whether it is better to start treatment with two drugs instead of one.



STAR*D focused on non-psychotic major depressive disorder (MDD) in adult outpatients. The primary purpose of this research study was to determine which treatments work best if the first treatment with medication does not produce an acceptable response. All participants at first received the selective serotonin reuptake inhibitor (SSRI) citalopram (open label). If symptoms remained after 8–12 weeks of treatment, up to four other levels of treatment were offered, including cognitive therapy and other medications (Table 1). There was no placebo treatment option.

The study involved a highly representative clinical sample of depressed outpatients. In that regard, the STAR*D population was different than the highly selective cohort usually enrolled in industry-sponsored clinical trials.

At each level change, participants were asked to indicate the unacceptability of the potential treatment strategies (eg, to augment or to switch medications). Participants were then be eligible for random assignment the next treatment options.

Level 2

Participants who either did not have an adequate response to or could not tolerate citalopram are eligible for Level 2. The Level 2 treatment strategies were:


i) Medication and Psychotherapy Switch: switch to sertraline, venlafaxine extended release (XR), bupropion sustained release (SR), or cognitive therapy (CT).
ii) Medication and Psychotherapy Augmentation: add to citalopram either a) buspirone, b) bupropion SR, or c) CT.
iii) Medication Only Switch or Medication Only Augmentation: options were available for participants for whom CT is
iv) Psychotherapy Only Switch or Psychotherapy Only Augmentation: options were available for participants for whom additional medication is unacceptable at this point in the study (participants must be willing to continue citalopram)


Level 2A

Participants without a satisfactory response to their Level 2 treatment were eligible for random assignment to additional treatment at Level 2A. Level 2A was included so that all participants entering Level 3 had an opportunity to respond to at least two medications. Level 2A consisted of medication switch to one of two antidepressants (venlafaxine XR or bupropion SR).


Level 3

Participants without satisfactory response to Level 2 and, if appropriate Level 2A, were eligible for random assignment to one of the following treatments:
i) Medication Switch to: a) mirtazapine or b) nortriptyline, a tricyclic antidepressant.
ii) Medication Augmentation: add (to current Level 2 or Level 2A medication) either: a) lithium or b) thyroid hormone (T3).


Level 4

Participants without an adequate response to Level 3 were eligible for random assignment to Level 4 treatment. Level 4 includes two medication switch options: to tranylcypromine (a monoamine oxidase inhibitor), or to mirtazapine plus venlafaxine XR.



The study, which cost $35 million, failed to find any significant differences between drugs at each step in terms of the primary outcome measure, which was remission of depression. While there have been other significant findings from the study, the data did inform practitioners about “next step” management of patients with who fail on initial therapy.

CO-MED, like the STAR*D trial, was National Institute of Mental Health sponsored.2 Completed in late 2009, the results of this research have not been published. In contrast to STAR*D, this study compared whether a combination of antidepressants is better than one antidepressant alone when administered as initial treatment for people with chronic or recurrent MDD. CO-MED was designed to test whether two different medications when given in combination as the first treatment step, compared to one medication, enhances remission rates, increases speed of remission, is well tolerated, and provides better sustained benefits in the longer term. There were two arms to the study.

In Arm A, one of the following were given along with placebo: bupropion, escitalopram, mirtazapine, or venlafaxine.

In Arm B, two of the following drugs were given in combination: bupropion, escitalopram, mirtazapine or venlafaxine (Table 2).

Hopefully, the results of CO-MED will prove less nihilistic than those of the STAR*D trial with respect to answering the major question: Which treatment works best? One of the more disappointing aspects of both studies is that neither one looked at the use of a second-generation antipsychotic as an add-on treatment. Given that we now have increasing use of these drugs to augment antidepressants, it would be reassuring to have comparative data on both the safety and effectiveness of this approach.



Perhaps the answers we are looking for in terms of predicting treatment response may not come from large comparative clinical trials, but from molecular psychiatry research.

I want to thank David A. Mrazek, MD, FRCPsych, for serving as guest editor for this issue. Pharmacogenomic testing, he observes, may soon become standard practice based on the patient-specific evidence base that already exists. The four articles in this issue that address progress in individualized molecular psychiatry hint at the possibility, he notes, that we will be able to abandon our traditional trial and error approach to medication selection and begin providing our patients safer and more effective individualized psychopharmacologic treatments.

I also direct your attention to an article by Racha Nazir, MD, and colleagues regarding advice on starting the outpatient clinic. It touches on practical issues as office design, charting, knowledge of pharmacotherapy and psychotherapy, and individualization of patient care.

This issue marks the introduction of a new bi-monthly column titled “Clinical Updates in Child & Adolescent Psychiatry” by Margaret D. Weiss, PhD. Dr. Weiss is the head of the Provincial ADHD Program and clinical professor at the University of British Columbia Children’s & Women’s Health Centre in Vancouver, Canada. The column will highlight the clinical approaches, science, and new developments in child psychiatry. I look forward to her contributions and hope our reader-practitioners find the information useful.  PP



1. Rush AJ. STAR*D: what have we learned? Am J Psychiatry. 2007;164(2):201-204
2. Combining Medications to Enhance Depression Outcomes (CO-MED). Available at: http://clinicaltrials.gov/ct2/show/NCT00590863. Accessed April 19, 2010.


Dr. Aggarwal is senior resident, Dr. D.D. Sharma is assistant professor, Dr. R.C. Sharma is professor and head, and Dr. Kumar is associate professor, all in the Department of Psychiatry at Indira Gandhi Medical College in Shimla, India.

Disclosure: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Ashish Aggarwal, MD, Senior Resident, Department of Psychiatry, Indira Gandhi Medical College, Shimla-171001, Himachal Pradesh, India; Tel: +91-0-9218832616; Fax: 91-177-2658339; E-mail: drashish1980@gmail.com.



Clozapine is an atypical antipsychotic used for treatment-resistant schizophrenia. It has also been used for other disorders, such as obsessive-compulsive disorder, especially as an augmenting agent. Paradoxically, there are few reports of clozapine-induced obsessive-compulsive symptoms (OCS). The authors report on a patient with schizophrenia who developed OCS twice when clozapine was initiated, and responded positively to lowering the dose of clozapine.

Focus Points

• Clozapine is the drug of choice for patients with treatment-resistant schizophrenia.
• Obsessive-compulsive symptoms (OCS) can occur during the course of schizophrenia.
• Clozapine can cause OCS in patients with schizophrenia.
• It is important to clarify the relation of OCS with antipsychotic medications, including clozapine, in patients with schizophrenia.
• Clozapine-induced OCS needs to be managed either by lowering the dose or adding an anti-obsessive medication like serotonin reuptake inhibitors. 



Clozapine is an atypical antipsychotic used for managing patients with treatment-resistant schizophrenia. Unlike other antipsychotics, it has potent antagonistic activity at the serotonin (5-HT)2 receptor and has less affinity for dopamine-2 receptors. Development of obsessive-compulsive symptoms (OCS) with atypical antipsychotics, including clozapine, have been reported in the literature.1,2 On the contrary, these atypical antipsychotics, including clozapine, have been used for the management of treatment-resistant obsessive-compulsive disorder (OCD).3,4 A large retrospective review5 did not find any worsening or emergence of OCS/OCD with clozapine treatment. The authors report on a patient with schizophrenia who developed OCS twice when clozapine was initiated, and responded positively to lowering the dose of clozapine.


Case Report

Mr. P, a 20-year-old unmarried male presented with a history of violent aggressive behavior, smiling and muttering to himself, suspiciousness, decreased sleep, and decrease in self care for the last 2 years. There was no significant past, family, or personal history. He was well adjusted premorbidly. He was diagnosed as a case of undifferentiated schizophrenia, as per the International Statistical Classification of Diseases and Health Related Problems, Tenth Revision.6 The patient was receiving treatment for the last 1.5 years but tended to be non-compliant. Currently, the patient had exacerbated his illness after he stopped treatment for 2 months. No records of his treatment were currently available. This time, he was started on olanzapine 10 mg/day increased to 20 mg/day, along with chlorpromazine 200 mg/day. There was no improvement at all for a period of ~3 weeks.

In view of marked aggression, adamant behavior, and hostility, the patient was started on clozapine 25 mg/day gradually increased to 250 mg/day over a period of 2 weeks; simultaneously, other drugs were gradually tapered over a period of 1 week. After ~5 days of clozapine 250 mg, it was observed that, in addition to previous symptoms, the patient also started doing things repeatedly. He would repeatedly touch some objects such as glass and doors and would get irritable if asked not to do so. He would lie down on the floor and, after a few minutes, would get up and repeat the cycle 4–5 times before finally lying on the bed. On asking, he would report that he felt compelled to do it again and again, although he knew that these actions were irrational and that he was doing this himself, without any external influence. The Yale-Brown Obsessive Compulsive Scale score was 20. Review of the patient’s treatment record revealed that ~8 months ago, he was started on clozapine, in view of non-response to haloperidol and risperidone in adequate doses for an adequate time period. The patient started developing similar OCS at that time when he was on clozapine 250 mg/day; however, thinking it to be related to psychosis, the dose of clozapine was increased further up to 400 mg/day, leading to further exacerbation of OCS. Capsule fluoxetine up to 40 mg/day was added to the treatment without much relief in the symptoms. Since the patient developed marked sedation and increased OCS, clozapine was stopped and the patient was started on trifluperazine and amisulpride at that time. The OCS remitted within a period of ~3 weeks.

In view of appearance of OCS at clozapine 250 mg/day on both occasions, it was decided to decrease the dose of clozapine to 200 mg/day, and amisulpride up to 400 mg/day was added to the treatment. The patient’s OCS decreased and subsided after ~1 week of decreasing the dose.



In this case, during both instances, the symptoms developed when a dose of clozapine >200 mg and abated on decreasing the dose. Alhough during the first scenario fluoxetine was also added, it did not lead to significant improvement in symptoms and the OCS improved after stopping clozapine. Thus, in this patient, OCS were definitely related to clozapine and were a dose-related phenomenon. This case differs from earlier reported cases of clozapine-induced OCS because the patient developed OCS after a short period of clozapine treatment (<3 weeks) and the patient developed OCS at clozapine 250 mg/day.

Previous reports of clozapine-induced OCS have been at comparatively higher doses of clozapine (300–900 mg/day)2,7,8 and after a long period of clozapine treatment (ranging from 10 weeks to 2 years).2,7-9 In adition, this patient did not have any OCS prior to clozapine treatment, though there have been reports of clozapine exacerbating already existing OCS in schizophrenia.2

A recent study10 of OCD in clozapine-treated patients with schizophrenia or schizoaffective disorder revealed a prevalence of 24% of clinically significant OCS. However, the temporal relationship between the onset of obsessional and schizophrenic symptoms and clozapine treatment was not established. Approximtely 50% of these patients had OCS prior to clozapine treatment.

Multiple hypotheses have been offered to explain the development of OCS during antipsychotic treatment. For clozapine-induced OCS, both 5-HT2A and 5-HT2C receptor antagonisms11 have been postulated to play a role in the generation of OCS. Other mechanisms that have been reported are the role of dopamine in the pathogenesis of OCS and the serotonergic modulation of dopaminergic system.12,13

It is important to clarify the relationship with antipsychotics while evaluating a patient of schizophrenia presenting with OCS. This is of importance for the management of such patients. Cases of spontaneous self-remission of clozapine-induced OCS within 1–3 weeks have also been described in the literature.14 Other options for clozapine-induced OCS include lowering the dose of clozapine as in this case, or adding a serotonin reuptake inhibitor. Switching to another antipsychotic might also be an option, but one should be careful for the exacerbation of psychosis as clozapine is generally used for treatment-resistant patients.



Given the paradoxical efficacy of clozapine in resistant cases with OCD, the overlapping neurobiology of OCD and psychosis, and the increasing use of clozapine for the management of treatment-resistant patients with schizophrenia, it is recommended that one should be vigilant and cautious while using clozapine. In addition, proper treatment history and delineation of symptoms in relation to drugs is important for correct management of patients and also to avoid polypharmacy.  PP



1.    Khullar A, Chue P, Tibbo P. Quetiapine and obsessive compulsive symptoms (OCS): case report and review of atypical antipsychotics induced OCS. J Psychiatry Neurosci. 2001;26(1):55-59.
2.    Chong SA, Wong KE. Clozapine and obsessive compulsive symptoms in schizophrenia. Hong Kong Journal of Psychiatry. 1996;6(1):45-47.
3.    Young CR, Bostic JQ, McDonald CL. Clozapine and refractory obsessive compulsive disorder. A case report. J Clin Psychopharmacol. 1994;14(3):209-211.
4.    Keuneman RJ, Pokos V, Weerasundera R, et al. Antipsychotic treatment in obsessive compulsive disorder: a literature review. Aust N Z J Psychiatry. 2005;39(5):336-343.
5.    Ghaemi SN, Zarate CA, Popli AP, Pillay SS, Cole JO. Is there a relationship between clozapine and obsessive-compulsive disorder?: a retrospective chart review. Compr Psychiatry. 1995;36(4):267-270.
6.    International Statistical Classification of Diseases and Health Related Problems. 10th rev. 2nd ed. Geneva, Switzerland: World Health Organization; 2004.
7.    Patel B, Tandon R. Development of obsessive compulsive symptoms during clozapine treatment. Am J Psychiatry. 1993;150(5):836.
8.    Rahman MS, Grace JJ, Pato MT, Priest B. Sertraline in the treatment of clozapine-induced obsessive-compulsive behavior. Am J Psychiatry. 1998;155(11):1629-1630.
9.    Levkovitch Y, Kronnenberg Y, Gaoni B. Can clozapine trigger OCD? J Am Acad Child Adoles Psychiatry. 1995;34(3):263.
10.    Mukhopadhaya K, Krishnaiah R, Taye T, et al. Obsessive-compulsive disorder in UK clozapine-treated schizophrenia and schizoaffective disorder: a cause for clinical concern. J Psychopharmacol. 2009;23(1):6-13
11.    Dursun SM, Reveley MA. Obsessive-compulsive symptoms and clozapine. Br J Psychiatry. 1994;165(2):267-268.
12.    Goodman WK, McDougle CJ, Price LH, et al. Beyond the serotonin hypothesis: a role for dopamine in some forms of obsessive-compulsive disorder? J Clin Psychiatry. 1990;51(suppl):36-43.
13.    Dewey SL, Smith GS, Logan J, et al. Serotonergic modulation of striatal dopamine measured with positron emission tomography (PET) and in vivo microdialysis. J Neurosci. 1995;15(1 pt 2):821-829.
14.    Patil, VJ. Development of transient obsessive-compulsive symptoms during treatment with clozapine. Am J Psychiatry. 1992;149(2):272.


Dr. Sharma is professor and head of psychiatry at Indira Gandhi Medical College & Hospital in Shimla, Himachal Pradesh, India. Mr. Thakur is surgeon at Civil Hospital Rampur in Shimla.

Disclosure: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Ravi C. Sharma, MD, Professor & Head, Department of Psychiatry, Indira Gandhi Medical College & Hospital, Shimla (171001), Himachal Pradesh, India.
Tel: 91-177-2844644; Fax: 91-177-2658339; E-mail: ravi82000@yahoo.com.



Acute urinary retention as a conversion symptom has received little attention in the literature and has been mostly considered as a diagnosis per exclusion. This is a case report of 20-year-old female who presented with acute retention of urine as a conversion symptom with strong psychological antecedents; she recovered completely by removing secondary gain, giving suggestions, and undergoing family counselling.



There is a scarcity of information in the literature about the cause and management of acute urinary retention in females in comparison to males.1 The causes of acute urinary retention can be divided into four etiologic groups: obstructive, neurologic, pharmacologic, and psychogenic.2 Females presenting with urinary retention in the absence of any identifiable neuro-anatomic cause for their symptom pose a diagnostic and management challenge and may be dismissed as psychogenic cases.3 The present case report highlights the importance of identifying and resolving psychological factors leading to acute urinary retention in a young female.

Case report

A 20-year-old unmarried female, student of class 12, presented in the Surgical Out Patient Department (OPD) of our hospital with the complaint of acute retention of urine. She gave a history of intermittent catheterization at the local primary health center thrice over the past 5 days after which she was referred to our hospital. There was no history of similar complaints in the past. Examination of the patient was unremarkable except for the palpable bladder. The patient was catheterized and investigated for retention of urine and urinary tract infection. Her urine routine as well as microscopic and culture examination were normal. Plain X-ray of the abdomen region, ultrasound of the abdomen, and pelvic organs were also normal. The patient was put on empirical treatment in the form of tablet ofloxacin 200 mg BID and hyoscine butyl bromide 10 mg TID, and was given a catheter-free trial which proved futile because she again developed retention. Psychiatric opinion was sought as the patient was not responding to the treatment, and urodynamic evaluation was planned.

Psychiatric evaluation revealed that the female who came from a rural nuclear family had been facing severe psychosocial stress due to her father who frequently used to quarrel with his wife and scold the patient quite often after consuming alcohol. Just a day prior to the onset of her symptoms, the patient’s father had created a ruckus in the house and had physically assaulted the patient. The patient was an average student and was described to be sincere, sensitive, and passive by nature. The initial mental state examination was unremarkable; however, on subsequent exploration the patient was found to be preoccupied with her ongoing family stress but was oblivious to her physical symptom (la belle indifference). In the absence of any evident physical cause for urinary retention and strong temporal association of the symptom with the family stress, the patient was diagnosed as a case of “Conversion Reaction” as per the International Classification of Diseases, Tenth Revision,4 criteria.

The secondary gain the patient was receiving from her relatives and medical professionals was minimized and she was given strong suggestions. She was also prescribed fluoxetine 20 mg/day along with alprazolam 0.25 mg at bed time. Her parents were counselled in detail and role of stress in the genesis of this symptom was explained. The father of the patient was enrolled for further evaluation and management of alcohol dependence in the psychiatry OPD. The patient’s catheter was removed the third day; she started passing urine normally and was discharged on the above medications with advice to follow up after 7 days in the psychiatry OPD. On follow-up visit the patient reported that she did not take any medications at home and was completely asymptomatic. The patient had been maintaining well even after 3 months of discharge when she last came for follow-up.



Urinary dysfunction due to psychogenic causes like conversion reaction and anxiety has been reported both in males and females.5 Psychogenic urinary retention has been described more frequently in young adult females with history of childhood enuresis and disturbed social backgrounds. Such patients have been frequently diagnosed as “hysteric,” with their symptom representing a displacement of unacceptable sexual wishes and impulse.6

In one study,7 psychogenic factors have been cited as the second important cause of retention of urine in females. The role of psychological disturbances in the genesis of acute and chronic urinary retention in females has also been reported by other authors.8-10 In the patient presented, there was no evidence of any physical or organic cause to explain her retention of urine, but there was a definite evidence of a family stressor preceding the development of this retention. Furthermore, the symptom resolved completely after appropriate suggestions, cutting down secondary gain, and family counseling. Therefore, the retention of urine in the present case qualifies to be labelled as conversion symptom.

The present case highlights the need for looking in to and resolving precipitating and or perpetuating psychological stressors also as a cause of acute urinary retention, especially in young females, before subjecting them to unnecessary urodynamic investigations and repeated catheterizations.  PP



1.    Barone JG, Berger Y. Acute urinary retention in females. Int Urogynecol J. 1993;4(3):152-156.
2.    Vander Linden EF, Venema PL. Acute urinary retention in women. Ned Tijdschr Geneeskd. 1998;142(28):1603-1606.
3.    Kavia RB, Datta SN, Dasgupta R, et al. Urinary retention in women: its causes and management. BJU Int. 2006;97(2):281-287.
4.    International Classification of Diseases. 10th rev. Geneva, Switzerland: World Health Organization; 1992.
5.    Sakakibara R, Uchiyama T, Awa Y, et al. Psychogenic urinary dysfunction: a uro-neurological assessment. Neurourol Urodynam. 2007;26(4):516-524.
6.    Bird JR. Psychogenic urinary retention. Psychother Psychosom. 1980;34(1):45-51.
7.    Kumar A, Banerjee GK, Goel MC, et al. Non-neurogenic, non-organic urinary retention in female: An indication for urodynamic evaluation. Indian Jl of Urol. 1996;12(2):55-59.
8.    Wheeler JS, Walter JS. Urinary retention in females: a review. Int Urogynecol J. 1992;3(2):137-142.
9.    Mosli HA, Farsi HM, Rimawi MH, et al. Retention of urine in females: causes and management. East Afr Med J. 1991 68(8):617-623.
10.    Sagar RS, Ahuja N. Psychogenic urinary retention. Am J Psychiatry. 1988;145(9):1176-1177.


This interview took place on November 30, 2009 and was conducted by Norman Sussman, MD.


Dr. Weintraub is Associate Professor of Psychiatry and Fellow at the Institute of Aging at the University of Pennsylvania in Philadelphia. His areas of research interest include the psychiatric and cognitive complications of Parkinson’s disease. Dr. Weintraub recently completed a 5-year Career Development Award from the National Institute of Mental Health titled “Depression Diagnosis and Treatment in Parkinson Disease.” In addition, he was coordinating investigator for a multi-site, international, industry-sponsored study of the frequency and correlates of impulse control disorders in Parkinson’s disease.


What is Parkinson’s Disease and Why Does Dementia with Lewy Bodies (DLB) Tend to get Clustered in with it in Discussions?

Parkinson’s disease is defined by its motor characteristics, whereas DLB is defined primarily by its cognitive and other non-motor deficits.

To meet criteria for idiopathic Parkinson’s disease, a person must have primary motor symptoms, the most common ones being tremor (upper extremity tremor in particular, usually asymmetric at the time of disease onset); bradykinesia, or slowness of movement; stiffness; and, at times, impairments in balance, although that tends to happen later in the course of the illness. Some combination of those types of motor symptoms is what helps patients meet criteria for Parkinson’s disease, often supported by a response to dopamine-replacement therapy.

In contrast, DLB is characterized at disease onset by a dementing illness consisting of impairment in memory and other cognitive abilities. Supporting features include psychotic symptoms, particularly visual hallucinations. Impairments in attention or fluctuations in alertness are also characteristic. Parkinsonism—some of the same features that I mentioned before—is also characteristic of DLB, although the response to dopamine-replacement therapy is typically less in DLB than in Parkinson’s disease.


Would it be confusing for a non-neurologist to distinguish between one or the other?

There is the potential for confusion. One main reason is that a fair number of Parkinson’s disease patients, even at the time of illness onset or diagnosis of motor symptoms, are already demonstrating some level of cognitive impairment.

The two can go hand in hand fairly early in the course of either illness, and therefore there is sometimes a blurring between diagnostic categories. Expert opinion is that if there is an established diagnosis of Parkinson’s disease and at least 1 year has gone by before the patient meets criteria for dementia, then the diagnosis is Parkinson’s disease dementia. If that dementia diagnosis either predates the onset of the motor symptoms or comes within the first year of the parkinsonism, then the patient would meet criteria for DLB.

The reason there seems to be so much overlap is that from a neuropathologic standpoint, the illnesses are very similar. The core neuropathology and even the brain regions that are affected appear to significantly overlap between Parkinson’s disease, Parkinson’s disease dementia, and DLB.


Compared to a decade ago, is there better understanding of the pathophysiology of Parkinson’s disease and DLB?

There has been some evolution in terms of understanding. One change to highlight over the past 10 years is that the neurotransmitter deficits really are beyond dopamine in Parkinson’s disease. The noradrenergic deficits are probably as significant or close to as significant as the dopaminergic deficits. In addition, serotonergic deficits can be prominent in the illness. However, it appears that all of the brain stem monoamines are affected to some degree in Parkinson’s disease, so it really is more than just a dopamine disorder.

Another prominent neurotransmitter deficit is in acetylcholine. The cholinergic deficits in Parkinson’s disease dementia are greater than in Alzheimer’s disease. Even non-demented Parkinson’s disease patients have significant cholinergic loss, so that probably helps explain the high frequency of cognitive impairments in Parkinson’s disease.


Have Anticholinergics been used to treat Parkinson’s Disease?

Yes, and they still are, though less commonly now. They have to be used cautiously in patients who are more likely to suffer the side effects of anticholinergics, which would include older patients or patients with preexisting cognitive impairment. Younger patients who are more intact cognitively still receive those treatments.


How Common are Parkinson’s Disease and DLB?

The primary risk factor for Parkinson’s disease and DLB is increasing age. Accurate prevalence and incidence estimates for Parkinson’s disease are hard to come by. The general estimate of Parkinson’s disease in the United States is anywhere between 500,000 and 1 million people. In Western societies, it is the second most common neurodegenerative disease after Alzheimer’s disease.

Looking at only the dementia end, DLB is thought to be the second most common dementing illness after Alzheimer’s disease. Part of the problems with the prevalence estimates are the overlapping diagnoses of DLB and Parkinson’s disease, so it is sometimes difficult to disentangle those two groups. Still, those are the general prevalence estimates. Increasing age is the main risk factor; however, compared with Alzheimer’s disease, it is not as uncommon for patients in their thirties, forties, or even fifties, to develop Parkinson’s disease, much more common relatively than in Alzheimer’s disease.


When people lose 80% of their neurons they get clinical manifestations of Parkinson’s Disease. Does everybody as they get older lose these neurons? Is it only a matter of time?

Parkinson’s disease is a disorder of aging. It is unclear if the incidence of Parkinson’s disease will peak at a certain age or whether it just continues to go up. All evidence to this point is that it continues to go up with advanced age. A person needs to lose ~80% of the neurons in the substantia nigra before clinically manifesting the motor symptoms of Parkinson’s disease. Another advancement in the past decade has been the work of Professor Heiko Braak and other neuropathologists that have not only staged Alzheimer’s disease, but also showed a staging process for Parkinson’s disease. Clearly, the brain stem changes in the majority of patients occur even before 80% of those neurons are lost in the substantia nigra, which helps explain some of the pre-motor symptoms that can occur. Beyond the substantia nigra in the later stages of the illness, the pathology spreads to cortical areas; by then it really becomes very much a diffuse brain disease.


Are there certain non-motor cognitive or psychiatric symptoms in Parkinson’s disease that will present before any movement disturbance is detected?

Yes, there has been significant research conducted in that area in the past decade, both from large European databases where patients are followed prospectively from young adulthood annually, as well as from case-controlled studies. There is now convincing evidence that patients with Parkinson’s disease compared to non-Parkinson patients are more likely to have a lifetime history of either depression or an anxiety disorder in the 5–10-year period, and perhaps even up to 20 years for anxiety, preceding the onset of Parkinson’s disease.

Another common psychiatric or non-motor disorder reported to occur prior to Parkinson’s onset is rapid eye movement behavior disorder, which is a parasomnia where patients are able to verbally or physically act out their dreams. This has been reported to occur up to 20 years prior to the onset of Parkinson’s disease. When most of us dream we are in an atonic state; we cannot physically or verbally act out our dreams. This atonia seems to be lost in a fair percentage of Parkinson’s patients, and apparently may be lost prior to the onset of Parkinson’s disease, which is thought to represent a brain stem dysfunction.

Other non-motor symptoms that have been reported to occur prior to Parkinson’s disease include impaired smell or olfaction, which is very common in Parkinson’s disease; constipation; and altered sympathetic intervention of the heart. All are testable.

What are some of the cognitive symptoms you observe in patients with Parkinson’s disease?

It was taught in the past that Parkinson’s disease patients compared with Alzheimer’s disease patients are less likely to have memory or language deficits and more likely to have deficits in other domains. For patients that have memory deficits, it is less likely to be an encoding deficit, as seen with Alzheimer’s disease, but more of a retrieval deficit, which was thought to reflect more subcortical dysfunction.

However, accumulating research has found that Parkinson’s disease patients can have impairments in a range of cognitive domains, including memory, attention, executive abilities, and visual-spatial abilities. This has been one major shift in the perception of the disease.

The other major shift is the recognition that, whereas cross-sectional studies have demonstrated that ~30% of Parkinson’s disease patients have dementia, more careful longitudinal studies1,2 have shown that the overwhelming majority of patients with Parkinson’s disease do develop dementia if followed long enough. Early stages of these deficits can be detectable often at the time of diagnosis in 20% of patients. If the clinician asks the right questions and uses appropriate assessment instruments, the disease can be detected early.


What kind of visual-spatial disturbances are involved?

A common example would be the judgment of line orientation tests, which is the ability to conceptualize lines in three dimensions, so to speak. However, it can be detectable even at a much simpler level, just with pentagon or clock drawing. Another difficulty for Parkinson’s patients is drawing a cube. The disease can be detected even on simple paper-and-pencil tests.

Are some subtle dysfunctions picked up early and more inevitable ones later on?

Yes. Heterogeneity is the one word that I use more than any to describe all the motor and non-motor features of Parkinson’s disease. There is such a range of presentations of Parkinson’s in patients from both a non-motor and a motor standpoint. This is one area where I think our research has failed us to some extent, in that most studies will present means and averages for patients on a particular score or domain; however, the individual presentation of patients is really lost that way. The means really mean less in Parkinson’s disease than how individual patients present.

Some patients do have cognitive deficits early on, and others do not for 15 years. Somebody may have a primary memory deficit, while another may have impairment in multiple domains. Presentations are all over the board.

Do treatments for psychiatric symptoms and Parkinson’s disease adversely affect each other?

This is a very controversial and complex area. Early in the course of Parkinson’s disease, a de novo case, for example, who has not been treated ever, often would respond with exposure to dopamine-replacement therapies, whether it is levodopa or dopamine agonists. For instance, some patients show improvements in psychomotor speed, attention, and concentration. However, the results are mixed, with some patients or cognitive abilities improving, and others worsening.  Thus, it is difficult to offer a generalization in this regard.

As patients advance in the course of their illness, where they age and the pathology becomes more severe, it seems more likely that the medications, if anything, are not beneficial to cognition. Rather, they may be potentially harmful, particularly with higher dosages when patients can become delirious or psychotic, which certainly has an effect on the cognition, as well.

Deep brain stimulation (DBS), which is increasingly used as a treatment for Parkinson’s disease, is thought to perhaps impair verbal fluency and some aspects of memory. That may be a complicating effect of that specific treatment. The anticholinergics and amantadine are probably the most notorious medications in terms of worsening cognition.

In terms of psychiatric medications, in general the newer antidepressants are thought to be safe and well tolerated from both a motor and cognitive standpoint. Recent studies show benefit for tricyclic antidepressants in Parkinson’s disease.3,4 One concern there, of course, is that with a heavier anticholinergic load, cognition could potentially worsen.

It is unclear from a cognitive standpoint whether antipsychotics have deleterious effects on Parkinson’s disease, but certainly there is concern about them worsening motor symptoms in Parkinson’s patients.

Finally, the last class of psychiatric medications commonly used is benzodiazepines. These medications must be used very cautiously in Parkinson’s disease patients because common side effects include impaired gait, sedation, and worsening cognition.

Are any therapies currently available for Alzheimer’s disease effective in improving cognitive symptoms in patients with Parkinson’s disease and DLB?

The cholinesterase inhibitor rivastigmine actually has Food and Drug Administration approval for the treatment of Parkinson’s disease dementia. This was on the basis of one large European study5 that showed significant, but modest, benefits in the treatment of Parkinson’s disease dementia, similar to what would be present in Alzheimer’s disease patients. A more recent placebo-controlled study6 in patients with both Parkinson’s disease dementia and DLB showed benefit for memantine. Those are really the two large-scale studies that have been positive to date for the treatment of cognitive dysfunction in Parkinson’s disease.

Another common non-motor disturbance in Parkinson’s disease is apathy, often in the context of cognitive impairment, but not always. We really do not have good treatments for apathy in the context of any other disorder. We extrapolate what people use in other populations, including the use of stimulants. Clinicians, myself included, may use methylphenidate and dextroamphetamine as a trial for apathy in particular. Bupropion is also used to some extent because of its stimulant-like properties, the reason being that it has some dopamine-enhancing effects, as well.

Have there been any meaningful advances in the treatment of the motor symptoms of these disorders in recent years?

The one class that was not available 10 years ago that is readily available now and used as a first-line agent in younger patients particularly are the dopamine agonists. The ones being used now are more selective and better tolerated overall than the older ones. This class of medication has been added to the armamentarium, in addition to levodopa, although levodopa still is the most potent in terms of its motor effects.

DBS has been a significant advancement, particularly for patients with more advanced disease, because those patients really had no option previously. Once they developed dyskinesias and other motor fluctuations, they were really at a dead end in terms of treatment. This often can be a successful treatment for patients that enables them to make a significant decrease in their dopamine-replacement therapy. Other fine tuning has been the increased use of catechol-O-methyl transferase inhibitors, that do allow a better management of motor fluctuations in off periods.

That being said, I think treatment has not advanced so significantly. I do think patients are better managed overall. Clinicians are able to go deeper into the course of their illness without significant complications compared with previously.


Does using these other, more indirect interventions delay some of the secondary complications of taking levodopa, such as the dyskinesias?

Yes. A preferred medication choice in this day and age would be to start with a dopamine agonist, or even for milder symptomatic benefit something like an monoamine oxidase-B inhibitor early in the course of the illness, and to delay the introduction of levodopa as long as possible.


Is there anything you would like to add?

One other interesting area for psychiatrists that has come to the forefront recently—and we have been involved in a fair amount of research with this—is impulse control disorders in response to dopamine agonist treatment. Parkinson’s patients can develop compulsive behaviors (the four that have been reported have been gambling, sexual behavior, buying, and eating) in connection with their Parkinson’s treatment. It is quite a problematic disorder, but also an interesting one from a psychiatric standpoint in that the disorder can be essentially induced by these dopaminergic medications. PP



1.    Aarsland D, Andersen K, Larsen JP, Lolk A, Kragh-Sørensen P. Prevalence and characteristics of dementia in Parkinson disease: an 8-year prospective study. Arch Neurol. 2003;60(3):387-392.
2.    Hely MA, Reid WG, Adena MA, Halliday GM, Morris JG. The Sydney multicenter study of Parkinson’s disease: The inevitability of dementia at 20 years. Mov Disord. 2008;23(6):837-844.
3.    Menza M, Dobkin RD, Marin H, et al. A controlled trial of antidepressants in patients with Parkinson’s disease and depression. Neurology. 2009;72(10):886-892.
4.    Devos D, Dujardin K, Poirot I, et al. Comparison of desipramine and citalopram treatments for depression in Parkinson’s disease: a double-blind, randomized, placebo-controlled study. Mov Disord. 2008;23(6):850-857.
5.    Emre M, Aarsland D, Albanese A, et al. Rivastigmine for dementia associated with Parkinson’s disease. N Engl J Med. 2004;351(24):2509-2518.
6.    Aarsland D, Ballard C, Walker Z, et al. Memantine in patients with Parkinson’s disease dementia or dementia with Lewy bodies: a double-blind, placebo-controlled, multicentre trial. Lancet Neurol. 2009;8(7):613-618.


Dr. Belleville is professor in the School of Psychology at Université Laval. Dr. Foldes-Busques is research associate at Centre Hospitalier Affilié Universitaire Hôtel-Dieu de Lévis. Dr. Marchand is professor in the Department of Psychology at the Université du Québec à Montréal.

Disclosures: The authors report no affiliation with or financial interest in any organization that may pose a conflict of interest.

Please direct all correspondence to: Geneviève Belleville, PhD, École de Psychologie, Pavillon Félix-Antoine-Savard, Bureau 1334, 2325, rue des Bibliothèques, Québec (Québec), G1V 0A6; Tel: 1-418-656-2131 ext. 4226; Fax: 1-418-656-3646; E-mail: Genevieve.Belleville@psy.ulaval.ca



Objective: The objective of this article is to describe the characteristics of patients with panic disorder from an emergency department by comparing them to patients with panic disorder from psychiatric settings on panic symptoms, psychiatric comorbidity, and psychological correlates of panic disorder.
Methods: Eighty-four consecutive patients consulting an emergency department with noncardiac chest pain and diagnosed as having panic disorder, and 126 patients with panic disorder seen in two specialized clinics for anxiety disorders, were assessed with validated clinical interview and questionnaires.
Results: Panic disorder patients recruited in the emergency department were older and reported fewer panic symptoms than their psychiatric settings counterparts. They also had less severe agoraphobic cognitions and less sensitivity to anxiety. The two samples displayed similar rates of psychiatric comorbidities and similar rates of suicidal ideation, with 24.3% to 31.3% of panic disorder patients overall having had thoughts of killing themselves.
Discussion: Panic disorder patients encountered in the emergency department tend to report physical, rather than psychological, symptoms of panic. This finding could explain the extremely low rates of panic disorder recognition in the emergency department.
Conclusion: Despite showing less severe panic symptoms, and sometimes no emotional or cognitive signs of fear at all, emergency department patients with panic disorder have elevated rates of psychiatric comorbidities and suicidal ideation and need adequate clinical attention.

Focus Points

• Male patients with panic disorder were more likely to be encountered in the emergency department of a general hospital than in clinics specialized in anxiety disorders.
• Patients with panic disorder from the emergency department displayed less numerous and severe panic symptoms, agoraphobic cognitions, and sensitivity to anxiety than patients with panic disorder from psychiatric settings.
• One-third of panic disorder patients from the emergency department had non-fear panic disorder, a condition characterized by the physical symptoms of panic but the absence of fear, whether of dying, losing control, or going crazy.
• Despite showing less severe symptoms, panic disorder patients from the emergency department had high rates of psychiatric comorbidity, particularly other anxiety disorders and major depressive disorder.
• In the emergency department sample, one panic disorder patient out of four had suicidal ideation within the past 7 days.



Chest pain is one of the 13 symptoms that may occur during a panic attack. It is the symptom most likely to prompt consultation at an emergency department.1 Accordingly, 17% to 32% of patients who consult an emergency department with chest pain have panic disorder.2-4 However, despite increasing knowledge about panic in the emergency room, panic disorder remains virtually unidentified.2

The discrepancy between the incidence of panic disorder in the emergency department and the emergency department professionals’ failure to detect it raises important questions regarding the clinical profile of panic disorder patients consulting in the emergency department. These patients may present a different profile compared to panic disorder patients encountered in psychiatric settings. Exploratory data have suggested that panic disorder patients from the emergency department are older, are more likely to be male, have less severe panic symptoms, and have lower rates of agoraphobia than their psychiatric counterparts.5 Reports of clinical experiences also suggested that it is likely for people with panic disorder to initially present to their general practitioner or hospital emergency department with a focus on somatic symptoms and concerns.6 These preliminary findings need to be replicated.

Another concern is the proportion of patients in the emergency department that appear to have a subtype of panic disorder, referred to as non-fearful panic disorder (NFPD). This subtype is characterized by no report of either fear of dying or fear of going crazy or losing control during panic attacks.7 In the emergency department of a hospital specialized in cardiology, Fleet and colleagues8 found that 44% of panic disorder patients seeking treatment for chest pain could be categorized as having NFPD. Using the National Comorbidity Survey database, Chen and colleagues9 found that 30% of panic attacks occurred without fear of dying or going crazy. The prevalence of this variant of panic disorder in the emergency department of general hospitals is not known.

The principal objective of the present study is to compare panic disorder patients from the emergency department versus in psychiatric settings on panic symptoms, psychiatric comorbidity, and psychological correlates of panic disorder. Another objective is to identify the proportion of patients displaying NFPD in a sample of panic disorder patients consulting for chest pain in an emergency department of a general hospital.



Participants and Procedure

The emergency department sample consisted of “quasi” consecutive patients consulting an emergency department with non-cardiac chest pain. Although efforts were made to approach every patient admitted to the emergency department with a complaint of chest pain on weekdays from 8am to 4pm, several patients (1,101 out of 3,234; 34%) could not be reached for various reasons (as described in the Figure). Inclusion criteria for the study were: ≥18 years of age, French or English speaking, and consulted the emergency department for chest pain non-associated with chest trauma. Exclusion criteria were: presented results outside the normal ranges on the electrocardiogram or blood tests, suggesting coronary artery disease; and presented a clear medical cause for the chest pain (eg, pulmonary embolism). Patients were assessed with self-report questionnaires and a clinical diagnostic interview conducted by a research assistant while they were in medical observation or waiting for tests results. Self-report questionnaires were completed on site or at home and returned to the research team with a prepaid envelope (if patients had insufficient time to complete the forms or if they were too tired). For the purpose of this study, the authors included data from participants meeting criteria for panic disorder based on the Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition.10 Significant interference with at least one area of functioning was defined by a clinical score of ≥4 on the Anxiety Disorder Interview Schedule for DSM-IV (ADIS-IV; n=84).11


The psychiatric settings sample was composed of 126 patients recruited for a panic disorder treatment delivered in a specialized anxiety clinic through newspapers and referrals by healthcare professionals. This sample included patients referred by family physicians, general practitioners and psychiatrists working in a psychiatric hospital, and psychiatrists working in a specialized anxiety clinic, as well as self-referred patients. Inclusion criteria were: 18–65 years of age; diagnosis of panic disorder with agoraphobia, based on DSM-IV criteria, for at least 1 year; onset of panic disorder prior to 40 years of age; and had not participated in cognitive-behavioral therapy for panic disorder within the last year. The severity of the disorder for the psychiatric settings sample was moderate to severe, interfering significantly with at least one area of functioning, in accordance with a clinical score of ≥4 on the ADIS-IV, and a score of ≥3 on the Global Assessment of Severity Scale. Following a telephone screening interview, all eligible patients completed an assessment battery and underwent a psychological assessment conducted by a research assistant. Patients were assessed using a clinical interview, and self-report questionnaires were completed before receiving treatment.




The ADIS-IV is a semi-structured interview assessing anxiety disorders according to DSM-IV criteria. It also includes a series of questions targeting mood, somatoform, and substance-related disorders. The ADIS-IV is widely used in research and clinical settings, and is considered a gold standard measure for the assessment of panic and other anxiety disorders.12 The ADIS-IV was used in both samples to screen and assess the severity of panic disorder and comorbid psychiatric diagnoses. A French version of this instrument was used, but no information on its psychometric validation is currently available. In the psychiatric settings sample, participants were also administered the Global Assessment of Severity Scale (GASS).13 The GASS is a clinician-administered five-point scale assessing impairment caused by panic and agoraphobic symptoms within the occupational, social, and recreational spheres.



The Beck Depression Inventory, Second Edition (BDI-II),14 includes 21 items that assess symptoms of depression; for each item, four statements describe increasing levels of symptom intensity. The respondent chooses the statement that best reflects his or her state of the last 7 days. The BDI-II has been extensively validated, and good psychometric properties have been reported for the French version used in this study.15 Item #9 (suicidal ideation) was singled out to assess suicidal ideation.



The Agoraphobic Cognitions Questionnaire (ACQ)16 measures the presence of 14 catastrophic thoughts related to panic (eg, “I will have a heart attack”; “I am going to go crazy”). Each thought is rated on a scale from one (very rarely) to five (very often). The total score ranges from one to five, and is computed by averaging the scores on the 14 items. Higher scores indicate greater frequency catastrophic thoughts. The French translation of the ACQ has demonstrated good internal consistency (a=.75) and temporal stability (r=.71).17



Anxiety Sensitivity Index (ASI)18 is a 16-item self-report questionnaire that assesses the way that respondents react to anxious arousal (eg, “It is important to me not to appear nervous”; “Unusual body sensations scare me”; “It scares me when I am nervous”). Each item is rated on a scale from zero (very little) to four (very much). Total score is obtained by summing the scores from each item and ranges from 0–64, with higher scores indicating greater sensitivity to anxiety. Psychometric properties of the French translation17 are adequate (internal consistency: a=.87; temporal stability: r=.91).


Data Analyses

A series of statistical analyses were performed to compare the emergency department and psychiatric settings samples. Mean differences on continuous variables (questionnaires scores) were assessed with independent t tests or Analysis of Variance (ANOVA) tests. Frequency differences on dichotomous variables (presence of symptoms and diagnoses) were evaluated with chi square analyses. Each analysis was tested with a .05 a-level. While no corrections were systematically conducted to adjust the a-level for multiple statistical tests, differences associated with a P value inferior to .05, .01, and .001 were distinctly reported. More importantly, effect sizes were computed each time a statistical test was associated with a P value <.05 in order to assess the strength of the association. Effect sizes of mean differences on continuous variables were evaluated using Cohen’s d (.2=small; .5=moderate; .8=large). Significant chi square analyses were followed by the calculation of Cramér’s V, a measure of the strength of the association between two categorical variables. A Cramér’s V between .20 and .25 reflects a moderate strength of association, and between .30 and .35, a strong one.



The sociodemographic characteristics of the participants in the emergency department and psychiatric settings samples are presented in Table 1. Significant differences were observed between samples regarding age, proportion of women to men, and level of education achieved. The emergency department sample was nearly equally composed of men and women (47.6% women), while the psychiatric settings sample had a greater proportion of women (77.0%). Patients from emergency department were, on average, 10 years older than patients from psychiatric settings (48.73 and 38.60 years old, respectively), and had a slightly higher level of education. To ensure that the age difference was not an artifact due to different selection criteria (18–65 years of age in the psychiatric settings sample versus ≥18 years of age in the emergency department sample), the comparison was repeated with participants >65 years of age (n = 13) removed from the emergency department sample. Participants in the emergency department sample were still significantly older than those from the psychiatric settings sample (44.48 vs. 38.60, respectively; P<.001).


Table 2 presents the frequency of DSM-IV panic attack symptoms reported by patients with panic disorder, ie, rated ≥4 on a zero-to-eight scale during the administration of the ADIS-IV, according to sample of origin. Eleven out of 13 symptoms were more frequently reported by psychiatric settings patients than by emergency department patients. Cramér’s V values ranged from .14 (fear of dying) to .50 (fear of losing control or going crazy), indicating effect sizes of moderate to large magnitude for most differences (Table 2). Only paresthesia was evenly encountered in both groups. Although participants from the emergency department sample consulted for chest pain, they may have reported not having it during panic attacks; thus, most (83.1%), but not every, panic disorder patients from the emergency department reported chest pain. On average, psychiatric settings patients reported three more symptoms during panic attacks than emergency department patients (9.21 vs. 6.61; Table 2).


Rates of psychiatric comorbidity among both samples are presented in Table 3. Agoraphobia was encountered in 32.1% of emergency department patients. The high prevalence of agoraphobia in the psychiatric settings sample (100%) only reflected the selection criteria used to recruit this sample. Rates of comorbid anxiety disorders were similar in both groups, with the exceptions of specific phobia and posttraumatic stress disorder (PTSD), which were more frequent among emergency department patients. Mood disorders, particularly major depressive disorder (MDD), were also more frequent among emergency department patients than among psychiatric settings patients (Table 3). Comorbid somatoform or substance-related disorders were rarely encountered in either group.


Further differences emerged regarding psychological aspects related to panic disorder (Table 4). Emergency department patients had lower ACQ and ASI scores, indicating less severe agoraphobic cognitions and less sensitivity to anxiety. Corresponding effect sizes were large. To ensure that the difference in ACQ scores was not an artefact due to different selection criteria (only participants in the psychiatric settings sample had to suffer from agoraphobia to be included in the study), the comparison was repeated with participants without agoraphobia (n=57) removed from the emergency department sample. Participants remaining in the emergency department sample still reported significantly lower ACQ scores than those from the psychiatric settings sample (2.019 vs. 2.649, respectively; P<.001). Severity of depressive symptomatology and presence of suicidal ideation were similar in both groups. BDI mean scores indicated the presence of mild depressive symptoms in both groups. Between 24.6% and 31.3% of all panic disorder patients reported suicidal ideation.


The characteristics of panic disorder patients that could be categorized as having NFPD, ie, that reported no fear of dying or of losing control during panic attacks, are reported in Table 5. The proportion of NFPD patients in the emergency department sample (32.1%) was almost three times that observed in the psychiatric settings sample (11.9%). In order to assess differences between panic disorder and NFPD while partitioning out the variance attributable to the sample of origin (emergency department or psychiatric settings), three 2X2 ANOVAs were performed, on the ACQ score, the ASI scores, and the number of “non-fear” panic symptoms. Independent variables were “type of panic disorder (panic disorder or NFPD)” and “sample of origin (emergency department or psychiatric settings).” NFPD patients had lower ACQ and ASI scores, as well as fewer panic symptoms. Interactions were not statistically significant, except for the ACQ scores. Inspection of the means indicated that the difference between panic disorder and NFPD patients was more important in the psychiatric settings sample than in the emergency department sample.



The objective of this study was to compare panic disorder patients from emergency department and psychiatric settings on panic symptoms, psychiatric comorbidity, and psychological correlates of panic disorder. Panic disorder patients recruited in the emergency department were older, reported fewer panic symptoms, and had less severe agoraphobic cognitions and less sensitivity to anxiety than their psychiatric settings counterparts. The two samples displayed similar rates of psychiatric comorbidities, with the exceptions of MDD, specific phobia, and PTSD, which were more frequent among patients from the emergency department. Both samples reported alarmingly high rates of suicidal ideation.

Fleet and colleagues5 compared panic disorder patients from the emergency department of a hospital specialized in cardiology to a sample recruited in psychiatric settings, with results that were very similar to those of the present study. This study’s findings were replicated regarding older age, low prevalence of agoraphobia in the emergency department, and the absence of difference in severity of depressive symptomatology and suicidal ideation. Adding to these findings, the authors observed that panic disorder patients from the emergency department reported fewer symptoms during their attacks, and that NFPD was more frequently encountered in the emergency department.

The reasons for the differences between the clinical portrait of panic disorder patients from the emergency department and panic disorder patients from psychiatric settings are not known. Observed differences may reflect the chronicity of panic disorder symptoms. Onset of panic disorder in psychiatric settings patients occurred at least 1 year prior to the study, while symptoms were present for at least the past month for the emergency department sample. Moreover, one of the most frequently cited reasons for consulting an emergency department during a panic attack is that the panic symptoms are part of a first episode, or that a new or more intense symptom has appeared.1 Panic disorder may develop progressively, with few symptoms during earlier panic attacks and increasing symptoms as the panic experience repeats itself over time. First episodes may lead patients to consult the emergency department because they believe their symptoms to be of organic origin. As they receive multiple negative results from medical exams and accumulate a history of impairment due to panic, patients with recurrent and aggravating panic attacks may be more likely to be directed toward mental health care. Early screening of these patients and referral to appropriate treatment could prevent this progression of symptoms. However, the stigma attached to mental illness may prevent emergency department patients from disclosing emotional symptoms, rendering even more difficult for emergency department physicians to recognize the emotional disorder causing chest pain.

The inclusion of NFPD patients may be an additional explanation for the appearance of less severe symptoms of panic disorder in emergency department patients. NFPD patients displayed genuine panic attacks, without reporting fear of dying or fear of going crazy or losing control. They also displayed less severe agoraphobic cognitions and less sensitivity to anxiety. Although these differences were observed in NFPD patients from psychiatric settings as well as from the emergency department, NFPD patients were nearly three times more likely to be encountered in the emergency department than in psychiatric settings. In fact, nearly one out of three (32.1%) panic disorder patients recruited in the emergency department could be categorized as having NFPD.

One implication of these findings is that, as a result of their less severe symptoms, infrequent manifestations of agoraphobia, less reported overall impairment, and a less “psychiatric” presentation, patients with panic disorder in the emergency room may not be adequately screened and offered appropriate therapeutic options. Indeed, recognition of panic disorder by healthcare providers has been associated with severity of fear experienced during the worse panic attack and overall symptom severity during the panic attack that led to consultation.19 Failure to recognize panic among chest pain patients is associated with serious consequences in terms of phobic avoidance, quality of life, and healthcare utilization.20-22 The current results have indicated that these patients suffer from significant depressive comorbidity, to an even greater degree than psychiatric patients, and that they present an elevated level of depressive symptomatology and suicidal ideation, replicating findings observed in their counterparts from psychiatric settings.21-23 In light of these data, it is essential that panic disorder be adequately identified and addressed and not merely considered as a residual category for noncardiac chest pain of unknown origin.

These findings are to be interpreted with caution as the study includes some methodologic limitations. First, due to the different settings, the selection criteria across both samples were not exactly the same. However, the authors performed statistical analyses on selected subsamples aiming to reduce the likeliness of rival explanations. Another limitation is that the emergency department sample did not include panic disorder patients that did not consult for chest pain (eg, patients consulting for hyperventilation, palpitations). As such, the observed differences may generalize only to panic disorder patients consulting the emergency department for chest pain. However, it has been observed that 91% of panic disorder patients presenting at an emergency department consult initially for chest pain.1 Finally, panic disorder patients without agoraphobia were not originally included in the psychiatric settings sample. This certainly explains the difference in prevalence of agoraphobia between the two samples (100% in psychiatric settings and 32.1% in emergency department). These figures do not reflect the true prevalence of agoraphobia among panic disorder patients in psychiatric settings. However, the fact that <33% of patients with panic disorder recruited in the emergency department reported agoraphobia is noteworthy.



This study added to earlier findings in demonstrating that panic disorder encountered in the emergency department presents different clinical characteristics than panic disorder seen in psychiatric settings. Despite reporting fewer and less severe symptoms than their counterparts from psychiatric settings, panic disorder patients consulting the emergency department for noncardiac chest pain presented a wide array of distressing symptoms and psychiatric comorbidities that warrant clinical attention, including suicidal ideation. There is a need for valid and “user-friendly” instruments to help emergency department physicians and nurses, who are not extensively familiar with psychiatric nosologies and subtle diagnostic particularities, to rapidly and efficiently identify panic disorder. Panic disorder is a treatable disorder; the efficacy and efficiency of interventions for panic disorder, whether cognitive-behavioral,24 pharmacologic,25 or a combination of both strategies,26 have been extensively demonstrated. Panic disorder patients could benefit from more sensitive panic disorder detection capacities in the emergency department, as well as a stronger bridge between emergency department healthcare providers and the mental health professionals that possess the therapeutic tools to help panic disorder patients.  PP



1.    Katerndahl DA. Factors associated with persons with panic attacks seeking medical care. Fam Med. 1990;22(6):462-466.
2.    Fleet RP, Dupuis G, Marchand A, Burelle D, Arsenault A, Beitman BD. Panic disorder in emergency department chest pain patients: prevalence, comorbidity, suicidal ideation, and physician recognition. Am J Med. 1996;101(4):371-380.
3.    Srinivasan K, Joseph W. A study of lifetime prevalence of anxiety and depressive disorders in patients presenting with chest pain to emergency medicine. Gen Hosp Psychiatry. 2004;26(6):470-474.
4.    Wulsin L, Liu T, Storrow A, Evans S, Dewan N, Hamilton C. A randomized, controlled trial of panic disorder treatment initiation in an emergency department chest pain center. Ann Emerg Med. 2002;39(2):139-143.
5.    Fleet RP, Marchand A, Dupuis G, Kaczorowski J, Beitman BD. Comparing emergency department and psychiatric setting patients with panic disorder. Psychosomatics. 1998;39(6):512-518.
6.    Austin D, Blashki G, Barton D, Klein B. Managing panic disorder in general practice. Aust Fam Physician. 2005;34(7):563-571.
7.    Beitman BD, Basha I, Flaker G, DeRosear L, Mukerji V, Lamberti J. Non-fearful panic disorder: panic attacks without fear. Behav Res Ther. 1987;25(6):487-492.
8.    Fleet RP, Martel JP, Lavoie KL, Dupuis G, Beitman BD. Non-fearful panic disorder: a variant of panic in medical patients? Psychosomatics. 2000;41(4):311-320.
9.    Chen J, Tsuchiya M, Kawakami N, Furukawa TA. Non-fearful vs. fearful panic attacks: a general population study from the National Comorbidity Survey. J Affect Disord. 2009;112(1-3):273-278.
10.    Diagnostic and Statistical Manual of Mental Disorders. 4th ed, text rev. Washington, DC: American Psychiatric Association; 2000.
11.    DiNardo PA, Brown TA, Barlow DH. Anxiety Disorders Interview Schedule for DSM-IV (ADIS-IV): Lifetime Version (ADIS-IV-L). San Antonio, TX: Psychological Corporation; 1994.
12.    Shear MK, Maser JD. Standardized assessment for panic disorder research. A conference report. Arch Gen Psychiatry. 1994;51(5):346-354.
13.    Mavissakalian M, Michelson L, Greenwald D, Kornblith S, Greenwald M. Cognitive-behavioral treatment of agoraphobia: paradoxical intention vs self-statement training. Behav Res Ther. 1983;21(1):75-86.
14.    Beck AT, Steer RA, Ball R, Ranieri W. Comparison of Beck Depression Inventories -IA and -II in psychiatric outpatients. J Pers Assess. 1996;67(3):588-597.
15.    Gauthier J, Morin C, Thériault F, Lawson JS. French adaptation of a self-administered measure of depression severity [French]. Revue Québécoise de Psychologie. 1982;3:13-27.
16.    Chambless DL, Caputo GC, Bright P, Gallagher R. Assessment of fear of fear in agoraphobics: the body sensations questionnaire and the agoraphobic cognitions questionnaire. J Consult Clin Psychol. 1984;52(6):1090-1097.
17.    Stephenson R, Marchand A, Lavallée MC. French-Canadian adaptation of the Agoraphobic Cognitions Questionnaire: cross-cultural validation and gender differences. Scandinavian Journal of Behaviour Therapy. 1999;28(2):58-69.
18.    Reiss S, Peterson RA, Gursky DM, McNally RJ. Anxiety sensitivity, anxiety frequency and the prediction of fearfulness. Behav Res Ther. 1986;24(1):1-8.
19.    Katerndahl DA. Predictors and outcomes in people told that they have panic attacks. Depress Anxiety. 2003;17(2):98-100.
20.    Katerndahl DA. Panic plaques: panic disorder & coronary artery disease in patients with chest pain. J Am Board Fam Pract. 2004;17(2):114-126.
21.    Roy-Byrne PP, Stein MB, Russo J, et al. Panic disorder in the primary care setting: comorbidity, disability, service utilization, and treatment. J Clin Psychiatry. 1999;60(7):492-500.
22.    Markowitz JS, Weissman MM, Ouellette R, Lish JD, Klerman GL. Quality of life in panic disorder. Arch Gen Psychiatry. 1989;46(11):984-992.
23.    Weissman MM, Klerman GL, Markowitz JS, Ouellette R. Suicidal ideation and suicide attempts in panic disorder and attacks. N Engl J Med. 1989;321(18):1209-1214.
24.    Otto MW, Deveney C. Cognitive-behavioral therapy and the treatment of panic disorder: efficacy and strategies. J Clin Psychiatry. 2005;66(suppl 4):28-32.
25.    Pollack MH, Doyle AC. Treatment of panic disorder: focus on paroxetine. Psychopharmacol Bull. 2003;37(suppl 1):53-63.
26.    Furukawa TA, Watanabe N, Churchill R. Combined psychotherapy plus antidepressants for panic disorder with or without agoraphobia. Cochrane Database Syst Rev. 2007(1):CD004364.

High Rates of Psychiatric Disorders Found in the Wives of Deployed Soldiers

Active military deployment can be a stressful period for both the family member on active deployment as well as family members at home waiting for a safe return. The mental health status of the wives of active military personnel, including those soldiers that are still at home and those that are deployed, has not frequently been studied.

Alyssa Mansfield, PhD, and colleagues reviewed the electronic medical records of >250,000 female spouses of active duty Army personnel receiving outpatient care between 2003 and 2006. Of the wives studied, ~31% had husbands that were currently home, ~34% were stationed overseas between 1–11 months, and 35% were deployed for >12 months.

Mansfield and colleagues found higher rates of mental health diagnosis in the wives of soldiers who were deployed for >12 months compared to those deployed for shorter periods of time or still stationed at home. The Table provides the adjusted analysis of wives whose husbands were not deployed and whose husbands were deployed between 1–11 months compared to the wives whose husbands were deployed for >12 months. When converting the excess cases to potential patients, Mansfield and colleagues found that the 41.3 excess cases would attribute to 3,474 mental health diagnoses and the 60.7 excess cases would attribute 5,370 mental health diagnoses.


Although there are limitations to this study, Mansfield and colleagues believe that this data proves that treatment options and preventive measures not only need to be offered to returning soldiers, but also to all military family members. (N Eng J Med. 2010;362(2):168-170.) –CN


Hypertension, White Matter Brain Lesions, and Dementia Risk in Older Women

Older women with hypertension may be at greater risk for abnormal white matter lesions in the brain that can cause dementia. The relationship between hypertension, blood pressure, and blood pressure control with white matter abnormalities in the Women’s Health Initiative (WHI) Memory Study—MRI Trial was studied by Lewis H. Kuller, MD, PhD, at the University of Pittsburgh.

The study’s sample included 1,403 women, ≥65 years of age, from the WHI study. All participants had no dementia at baseline and received blood pressure, cognitive, and magnetic resonance imaging (MRI) assessments.

According to MRI, women receiving hypertension treatment, with blood pressure ≥140/90 mm Hg, had the greatest number of abnormal white matter lesions. Women receiving no hypertension treatment, with blood pressure ≥140/90 mm Hg, had “intermediate” levels of abnormal white lesions. The white matter lesions were more likely to appear in the frontal lobe, compared to the occipital, parietal, or temporal lobes, and baseline blood pressure was strongly associated with white matter lesion volumes.

Previous evidence, combined with the current study, continues to suggest that maintaining health blood pressure levels consistently and sooner in life is the best preventive measure against dementia.

The WHI program is funded by the National Heart, Lung, and Blood Institute of the National Institutes of Health. (J Clin Hypertens. Epub Dec. 16, 2009) –LS


Sudden Infant Death Syndrome Linked to Lower Levels of Serotonin

Sudden infant death syndrome (SIDS) is the leading cause of postneonatal infant death in the United States. During a critical developmental period, SIDS is speculated to result from abnormalities in brainstem control of autonomic function and breathing. It has been reported that irregularities of serotonin (5-HT) and tryptophan hydroxylase (TPH2) receptor binding in regions of the medulla oblongata have been documented in infant deaths resulting from SIDS.

The hypothesis that SIDS is connected with reductions in tissue levels of 5-HT, TPH2, or both was tested by Jhodie R. Duncan, PhD, and colleagues at the Children’s Hospital Boston and Harvard Medical School in Massachusetts. For biochemical analysis, the study involved 35 infants who had died from SIDS, five infants with acute death from known causes, and five hospitalized infants with chronic hypoxia-ischemia. Through autopsy, tissue samples were obtained and several enzymes, including 5-HT and TPH2, were analyzed and measured.

In the raphé obscurus and the paragigantocellularis lateralis regions of the brain, the researchers found that 5-HT levels were 26% lower in SIDS cases compared with age-adjusted controls. TPH2 levels were 22% lower in the raphé obscurus in the SIDS cases, and 5-HT levels were 55% higher in the raphé obscurus and 126% higher in the paragigantocellularis lateralis in the hospitalized group compared with the SIDS group.

According to the authors, SIDS can be viewed as possibly being caused by a defect in one or more parts of the medullary 5-HT system.

Funding for this research was provided by Children’s Hospital Boston and Harvard Medical School in Massachusetts.  (JAMA. 2010;303(5):430-437). –JV

Psychiatric dispatches is written by Christopher Naccari, Lonnie Stoltzfoos, and Jennifer Verlangieri.