Dan W. Haupt

The metabolic effects of antipsychotic medications.

Objectives: To review current evidence for the hypothesis that treatment with antipsychotic medications may be associated with increased risks for weight gain, insulin resistance, hyperglycemia, dyslipidemia, and type 2 diabetes mellitus (T2DM) and to examine the relation of adiposity to medical risk. Methods: We identified relevant publications through a search of MEDLINE from the years 1975 to 2006, using the following primary search parameters: “diabetes or hyperglycemia or glucose or insulin or lipids” and “antipsychotic.” Meeting abstracts and earlier nonindexed articles were also reviewed. We summarized key studies in this emerging literature, including case reports, observational studies, retrospective database analyses, and controlled experimental studies. Results: Treatment with different antipsychotic medications is associated with variable effects on body weight, ranging from modest increases (for example, less than 2 kg) experienced with amisulpride, ziprasidone, and aripiprazole to larger increases during treatment with agents such as olanzapine and clozapine (for example, 4 to 10 kg). Substantial evidence indicates that increases in adiposity are associated with decreases in insulin sensitivity in individuals both with and without psychiatric disease. The effects of increasing adiposity, as well as other effects, may contribute to increases in plasma glucose and lipids observed during treatment with certain antipsychotics. Conclusion: Treatment with certain antipsychotic medications is associated with metabolic adverse events that can increase the risk for metabolic syndrome and related conditions such as prediabetes, T2DM, and cardiovascular disease.

Prevalence and predictors of lipid and glucose monitoring in commercially insured patients treated with second-generation antipsychotic agents.

OBJECTIVE The authors sought to quantify plasma lipid and glucose testing rates in patients receiving second-generation antipsychotics before and after guidelines recommending testing were issued in February 2004 by the American Diabetes Association (ADA). METHOD In this retrospective cohort analysis using data from a large managed care database (PharMetrics, 2000-2006), patients under age 65 on second-generation antipsychotics were identified and followed from 40 days before to 130 days after the antipsychotic prescription was written. Baseline and 12-week (40 days) lipid and glucose testing rates were determined for pre- and postguideline cohorts. Logistic regression analyses determined predictors of baseline and 12-week lipid and glucose testing while controlling for covariates. RESULTS A total of 5,787 preguideline patients and 17,832 postguideline patients were identified. Baseline lipid testing rates were 8.4% for the preguideline cohort and 10.5% for the postguideline cohort, and the 12-week testing rates were 6.8% and 9.0%, respectively. Baseline glucose testing rates were 17.3% for the preguideline cohort and 21.8% for the postguideline cohort, and the 12-week testing rates were 14.1% and 17.9%, respectively. All four comparisons were statistically significant. Baseline and 12-week testing rates for lipids and glucose in children were the lowest of all age groups. CONCLUSIONS Despite statistically significant improvements after the ADA guidelines were issued, monitoring for plasma lipids and glucose in this population remains low. Clinicians and administrators responsible for the health of at-risk populations should implement new approaches for effective monitoring of major modifiable risk factors for medical morbidity and mortality in patients taking second-generation antipsychotics.

Differential metabolic effects of antipsychotic treatments

Metabolic abnormalities such as obesity, diabetes and dyslipidaemia increase the risk of cardiovascular disease, as well as a number of other adverse long-term health consequences. There is increasing evidence from case studies, retrospective analyses and clinical trials to suggest that second-generation antipsychotics can increase the risk of metabolic abnormalities in patients with schizophrenia, with indications that the level of risk may vary among antipsychotic medications. Comparison of weight gain data for the second-generation antipsychotics provides strong evidence to indicate differences in the weight gain liability, with clozapine and olanzapine being associated with the greatest weight gain over 1 year. Data suggest that these treatment-induced changes in weight are primarily responsible for treatment-related changes in glucose metabolism; however, there is also evidence to suggest that some impairments in glucose metabolism may be independent of adiposity. Studies investigating the effects of atypical antipsychotics on glucose metabolism have used a number of techniques of varying sensitivity and quality in an attempt to assign causality. Recent studies using gold standard methodologies, for both insulin sensitivity and adiposity, have shown that psychiatric patients receiving antipsychotics are at least as sensitive to the adverse effects of adiposity on glucose and lipid metabolism as non-psychiatric controls. This demonstrates the importance of weight gain prevention in psychiatry to help reduce long-term risk. There is also growing evidence to suggest that the differential effects of second-generation antipsychotics on metabolic parameters also result in differences in the risk of metabolic syndrome, with olanzapine having a significantly higher risk than either aripiprazole or ziprasidone. This differential risk highlights the need for adequate monitoring in patients receiving treatment with second-generation antipsychotics and careful selection of treatment in high-risk patients.

Plasma Leptin and Adiposity During Antipsychotic Treatment of Schizophrenia

Alterations in plasma leptin have been reported in schizophrenia patients treated with antipsychotics, suggesting the hypothesis that impairments in leptin secretion or signaling might play a role in antipsychotic-induced weight gain. Plasma leptin was measured in 72 schizophrenia patients chronically treated with olanzapine (n=27), risperidone (n=24) or typical antipsychotics (n=21) and 124 healthy adult control subjects. ANCOVA was used to test effects of adiposity (body mass index kg/m2; BMI), subject group (treated patients vs untreated controls), and treatment group (specific medication groups and untreated controls) on plasma leptin concentrations. Additional analyses were performed in a subset of patients and controls individually matched for BMI to further assess group differences in plasma leptin independent of adiposity. BMI strongly predicted plasma leptin concentrations in the overall sample. In addition, a significant three-way interaction between BMI, subject group, and gender was observed. In the individually BMI-matched sample, modestly reduced plasma leptin levels (effect size 0.4 SD) were observed in treated patients in comparison to the BMI-matched healthy controls, with both groups including males and females. However, no differences in plasma leptin levels were observed in the matched sample when separately comparing male patients vs untreated male controls and female patients vs untreated female controls. Plasma leptin in chronically treated patients with schizophrenia is strongly predicted by adiposity, similar to untreated healthy individuals despite adequate power to detect a difference. The results argue against a role for defective leptin secretion or sensitivity in the weight gain induced by antipsychotic medications.

Abnormalities in glucose regulation associated with mental illness and treatment

Several major mental illnesses, including depression, schizophrenia, Alzheimer’s dementia and bipolar affective disorder have been associated with impaired glucose regulation and elevated rates of diabetes mellitus [1]. The risk factors and underlying causes for developing diabetes mellitus in the setting of a preexisting mental illness, or for developing a mental illness in the setting of preexisting diabetes mellitus, are incompletely understood. In the past several years, investigators have begun to focus on some of the disease, lifestyle and treatment factors that may contribute to this important comorbidity. Research in this area has also begun to stimulate clinical efforts to improve the identification and management of patients who suffer from these combined disease processes. Of the mental disorders associated with diabetes, depression and schizophrenia are clinically important and wellstudied disorders that affect significant portions of the population. Major depressive disorder is thought to affect approximately 6% of the population at some time in their lives and is associated with recurrence and intermittent or chronic treatment with antidepressant medications. Schizophrenia affects approximately 1% of the population and typically has a young adult age of onset. This is usually a chronic condition, punctuated by acute psychotic exacerbations and often requires lifetime treatment with antipsychotic medications. Due to high rates of depression in schizophrenia, as well as a growing trend toward polypharmacy in this practice setting, many patients with schizophrenia are treated with combinations of antipsychotic agents, antidepressants and other agents. Complicating our understanding of the association between diabetes and mental illnesses are reports indicating that many of the medications used to treat conditions such as depression and schizophrenia can contribute to changes in whole-body glucose metabolism. Reviewed below, for example, antipsychotic medications may contribute to exacerbations of existing types 1 and 2 diabetes, new onset cases of type 2 diabetes, dyslipidemia (e.g., hypertriglyceridemia) and cases of metabolic acidosis or ketosis. Clinically important questions, including the identification of risk factors and underlying mechanisms, appropriate screening and prevention approaches, and optimal treatment, all remain to be answered. Proposed mechanisms of action for medication effects on glucose metabolism will be briefly reviewed.

Adiposity and insulin sensitivity derived from intravenous glucose tolerance tests in antipsychotic-treated patients.

Cardiovascular disease is more common in schizophrenia patients than in the general population, with a hypothesized contribution from increases in adiposity produced by antipsychotic medications. We sought to test the relationship between adiposity and insulin resistance using frequently sampled intravenous glucose tolerance tests (FSIVGTTs) to quantify whole-body insulin sensitivity in chronically treated patients with schizophrenia or schizoaffective disorder and untreated healthy controls. FSIVGTTs, body mass index (BMI), and waist circumference were obtained in nondiabetic patients (n=63) receiving olanzapine, risperidone, ziprasidone, or first generation antipsychotics, as well as in healthy controls (n=14). Subject groups (including untreated healthy controls) were matched for BMI and all treated patient groups were additionally matched for age. Bergmans minimal model (MinMod) was used to calculate insulin sensitivity (SI), as well as secondary measures of interest. BMI and waist circumference significantly predicted insulin sensitivity measured as MinMod SI (F(1,62)=35.11, p<0.0001 and F(1,46)=24.48, p<0.0001, respectively). In addition, BMI and waist circumference significantly predicted the acute plasma insulin response to the glucose challenge (AIRG), consistent with a β cell compensatory response to insulin resistance (MinMod AIRG F(1,65)=22.42, p<0.0001 and F(1,49)=11.72, p=0.0013, respectively). Adiposity levels occurring during antipsychotic treatment are strongly related to insulin resistance, confirming that antipsychotic-induced weight gain can contribute to increased cardiometabolic risk in this population.

Perceptions of weight gain and bipolar pharmacotherapy: results of a 2005 survey of physicians in clinical practice

ABSTRACT Objective: To assess the perceptions of clinicians in the psychiatric community about pharmacotherapy and its impact on weight gain and adverse metabolic effects in patients with bipolar disorder. Methods: In November 2005, self-administered questionnaires were sent to 7000 psychiatrists who treat bipolar disorder in their clinical practice. An additional mailing of these questionnaires was sent in January 2006 to a different group of 7000 psychiatrists who treat bipolar disorder in their clinical practice. The first 298 completed surveys were analyzed. Results: Almost half of the respondents (48%) were psychiatrists in individual private practice and 32% were in community mental health centers. About two-thirds of respondents reported that 30–60% of their bipolar patients were overweight. Thirty-eight percent of respondents reported metabolic syndrome present in 20–40% of their patients. Almost all respondents (96%) reported a 20 lb increase in patients’ weight as a troublesome potential adverse event associated with the use of some agents. After initiating a new medication, more than 80% of respondents monitored their patients’ weight, fasting plasma glucose level, and fasting lipid profile at regular intervals. However, 80% did not monitor waist circumference. Overall, respondents viewed several agents (aripiprazole, ziprasidone, carbamazepine, and lamotrigine) as not (or minimally) problematic in terms of weight gain and adverse metabolic concerns. Clozapine and olanzapine were viewed as highly problematic due to their propensity to induce weight gain and negatively influence lipid and glucose metabolism. Other agents considered to be minimally to moderately problematic in terms of weight gain and metabolic issues were quetiapine, risperidone, lithium, and valproate. Respondents reported that the profile of a bipolar agent in terms of weight gain and adverse metabolic effects was an important consideration in the management of bipolar disorder. Conclusion: Although the study is limited by a low response rate and self-selection of respondents, clinicians who did respond were concerned about the risks of weight gain and metabolic disturbances in their patients treated with bipolar agents. For most parameters, such concerns were being integrated into clinical care. However, it appears that there is a need to increase clinicians’ appreciation of the importance of abdominal obesity and the need to monitor waist circumference. A growing recognition of the differences in weight-gain potential and adverse metabolic effects among agents appears to have had a definite impact on prescribing patterns in the management of bipolar disorder.

Reply: Plasma Leptin and Antipsychotic-Induced Body Weight Gain

We appreciate the comments of Dr Monteleone and colleagues and share their interest in the hypothesis that variations in leptin signaling early in the course of antipsychotic treatment could contribute to variance in weight gain observed during treatment. They mention their own previously published study that detected a significant inverse correlation between plasma leptin early in the course of treatment and subsequent weight change, with higher leptin levels associated with lower weight increases (Monteleone et al, 2002). However, neither their study nor the studies cited in their paper included the control group necessary to test the implicit hypothesis mentioned above. By way of background, individuals are hypothesized to experience a counter-regulatory increase in plasma leptin during weight gain, based on the established role of leptin as a satiety signal in rodents (Schwartz et al, 2000). The missing studies that we mention in our paper, which have not been reported to date, would address the question of whether leptin signaling during antipsychotic-induced weight gain is appropriate for the level of adiposity achieved by treated individuals. It is likely that many people experience counter-regulatory plasma leptin increases during weight gain that serve to discourage further weight gain. To test the hypothesis that antipsychotic weight gain is secondary to abnormal leptin secretion or signaling, one could perform a study consisting of prospective randomized assignment to an antipsychotic drug treatment expected to produce weight gain, to a negative control condition (placebo or antipsychotic not associated with weight gain), and, most importantly, to a positive control condition such as excess feeding with no change in medication. The comparison of interest would be between the two conditions where weight increased, in order to evaluate whether leptin signaling (eg crudely measurable in vivo in humans via plasma leptin) is overor underelevated as compared to plasma leptin elevations seen during weight gain due to simple increase in caloric intake. If plasma leptin was underelevated compared to excess feeding, this might suggest that antipsychotic treatment may interfere with leptin secretion or clearance, in either case interrupting normal leptin signaling that might otherwise reduce treatment-associated weight gain. With sufficient sample size, one could further evaluate whether individual differences in plasma leptin during antipsychotic-induced weight gain could help to explain which subjects experience more or less weight gain. Previous reports have not offered either the important control conditions or sufficient sample size to appropriately test these questions. Unfortunately, all these suggested studies would be time consuming and expensive to conduct. Given our inability to detect inappropriate plasma leptin levels in antipsychotictreated patients in comparison to adiposity-matched controls, the case for undertaking these subsequent studies is weakened (Haupt et al, 2005). As stated in our paper, along with the recent report by Herran et al, evidence does not currently support the hypothesis that leptin regulation in schizophrenia patients during antipsychotic treatment, as compared to leptin regulation in untreated healthy controls, is due to impaired leptin secretion or leptin resistance (Haupt et al, 2005; Herran et al, 2001).

Hypothesis 3. Depression is associated with hyperglycemia and other metabolic abnormalities.

Lustman PJ, Anderson RJ, Freedland KE, de Groot MK, Carney RM, Clouse RE: Depression and poor glycemic control: a meta-analytic review of the literature. Diabetes Care 23:934–942, 2000 Evidence that depression is associated with hyperglycemia and diabetes spans case reports and series, cross-sectional studies, and randomized clinical trials. Several reports describe peripheral insulin resistance and hyperinsulinemia in individuals with depression.16–18 Chiba et al.19 reported that depressed nondiabetic patients had decreased insulin sensitivity compared to nondepressed nondiabetic controls. Okamura et al.20 studied 20 nondiabetic depressed patients with oral and frequently sampled intravenous glucose tolerance tests before and after treatment with tricyclic antidepressants. They observed that non-diabetic depressed patients had decreased insulin sensitivity compared to nondepressed nondiabetic control subjects. After treatment, the patients with depression showed significant increases in insulin sensitivity. Lustman et al. performed this metaanalytic review of the literature in order to help clarify whether depression is associated with poor glycemic control. Studies published within the 25-year period before the meta-analysis were screened for inclusion. Included studies were limited to those that used adult participants and collected hemoglobin A1c (A1C) and depression information at the time of study assessment. Studies were excluded from the meta-analysis if they had fewer than 25 participants, were not available in English, or collected only a history of depression. Using established meta-analytic …