John W. Goethe

EEG coherence and power in the discrimination of psychiatric disorders and medication effects

Electroencephalogram (EEG) coherence (COH) and power measures were included in a series of stepwise discriminant analyses to determine which variables were most sensitive in the differentiation of four psychiatric inpatient groups and two major classes of psychotropic medication. Eight channels of eyes-closed, bipolar EEG activity were recorded from 74 inpatients (paranoid schizophrenics, dysthymics, major affectives receiving tricyclics, neuroleptics, or no medication, and geriatrics). Discriminant analyses were conducted for theta, alpha, and fast beta frequency bands for power variables, COH variables, and the resultant significant power and COH discriminating variables. Without exception, COH measures, usually in the alpha band, were more sensitive than power measures in differentiating the various groups. Results suggested that COH decreases with age, is greatest in paranoid schizophrenics, decreases with neuroleptic medication, and increases with tricyclic antidepressants. Group differences were interpreted in accordance with an arousal model for COH.

Characteristics of people lost to attrition in psychiatric follow-up studies.

In a large (N = 1,744) study of previously hospitalized psychiatric patients, multiple follow-up attempts were made to contact the ex-patients over a 1-year period after their discharges. When contacted they were asked to provide information about their posthospital adjustment; 59.5% of the sample was reached at least once and usable data obtained either in a telephone interview or from a mailed survey form. The contacted and noncontacted people represented very different subpopulations, both demographically and in terms of typical psychiatric descriptors. Those who were of lower socioeconomic status, male, unmarried, racial minorities, and those with records of substance abuse or assaultiveness, and who were generally more severely impaired during the baseline hospitalization were underrepresented in the contacted group. Possible reasons for these sample biases, the implications for hospitals conducting outcome assessments (i.e., for research and program evaluation purposes), and strategies for dealing with this kind of methodological problem are discussed.

Physiogenomic comparison of weight profiles of olanzapine- and risperidone-treated patients

Atypical antipsychotics induce pre-diabetic symptoms in some but not all patients, characterized most notably by elevated weight. The side effect profiles of the various drugs in the class differ, however, raising the possibility of drug-specific mechanisms for similar side effects. We used physiogenomic analysis, an approach previously employed to study the genetics of drug and diet response, to discover and compare genetic associations with weight profiles observed in patients treated with olanzapine and risperidone as an approach to unraveling contrasting mechanistic features of both drugs. A total of 29 single nucleotide polymorphisms (SNPs) were selected from 13 candidate genes relevant to two potential pharmacological axes of psychotropic-related weight profiles, appetite peptides and peripheral lipid homeostasis. We applied physiogenomic analysis to a cross-section of 67 and 101 patients being treated with olanzapine and risperidone, respectively, and assessed genetic associations with the weight profiles. Weight profiles in patients treated with olanzapine were significantly associated with SNPs in the genes for apolipoprotein E, apolipoprotein A4 and scavenger receptor class B, member 1. Weight profiles in patients treated with risperidone were significantly associated with SNPs in the genes for leptin receptor, neuropeptide Y receptor Y5 and paraoxonase 1. These results are consistent with contrasting mechanisms for the weight profile of patients treated with these drugs. Genes associated with olanzapine weight profiles may be related to peripheral lipid homeostatic axes, whereas those associated with risperidones may be related to brain appetite peptide regulation. Future physiogenomic studies will include neurotransmitter receptor SNPs and validation in independent samples.

The association between self-reported anxiety symptoms and suicidality

This cross-sectional study assessed the association between self-reported anxiety symptoms and self-reported suicidality among a mixed diagnostic sample of psychiatric outpatients. Data were obtained from chart review of 2,778 outpatients who completed a routine diagnostic clinical interview and a standardized self-report of psychiatric symptoms on admission. Bivariate analyses indicated that those with ≥ moderate anxiety symptoms were over three times as likely to report ≥ moderate difficulty with suicidality. Self-reported anxiety symptoms were associated with a 2-fold increased likelihood of reporting suicidality after controlling for confounding (demographics, depressive symptoms, and diagnoses). These data are consistent with a growing literature demonstrating an association between anxiety symptoms and suicidality, and suggest that this association is not accounted for by coexisting mood symptoms or diagnoses. A single item, self-report may be a useful screening tool for symptoms that are pertinent to assessment of suicide risk.

The effect of metformin on anthropometrics and insulin resistance in patients receiving atypical antipsychotic agents: a meta-analysis.

CONTEXT In the Clinical Antipsychotic Trials of Intervention Effectiveness, atypical antipsychotics (AAPs) were found to be associated with weight gain and impairment of glucose metabolism. While metformin has been shown to attenuate weight gain and insulin resistance, not all studies have shown a benefit in the reduction of antipsychotic-induced weight gain and insulin resistance. OBJECTIVE To characterize metformins impact on anthropometrics and insulin resistance in patients taking AAPs. DATA SOURCES A systematic literature search of MEDLINE, EMBASE, and Cochrane CENTRAL was conducted from the earliest possible date through December 31, 2008. The search was performed using the following Medical Subject Headings and text keywords: metformin, biguanide(s), in combination with neuroleptic(s), neuroleptic drug(s), antipsychotic(s), dopamine antagonist(s), atypical antipsychotic(s), psychotropic(s), risperidone, olanzapine, quetiapine, ziprasidone, sulpiride, clozapine, iloperidone, aripiprazole, paliperidone, melperone, bifeprunox, amisulpride, zotepine, and sertindole. STUDY SELECTION Six of 62 identified studies (N = 336 participants) met our inclusion criteria: randomized, placebo-controlled trials of metformin in patients taking AAPs with data on weight, body mass index (BMI), waist circumference, insulin resistance (determined using the homeostasis model assessment of insulin resistance [HOMA-IR]), and/or a diagnosis of diabetes. DATA EXTRACTION Data were independently abstracted by 2 investigators; disagreements were resolved through discussion or by a third investigator using a standardized data abstraction tool. For continuous endpoints, the weighted mean difference (WMD) of the change from baseline with 95% CI was calculated as the difference between the mean in the metformin and placebo groups. For categorical endpoints, the pooled relative risk (RR) with 95% CI was calculated. A random-effects model was used for all analyses. DATA SYNTHESIS Compared to placebo, the metformin group had significantly reduced weight (WMD, 3.16 kg; P = .0002), BMI (WMD, 1.21 kg/m²; P = .0001), waist circumference (WMD, 1.99 cm; P = .005), and HOMA-IR (WMD, 1.71; P = .004). The reduction in risk of diabetes was not statistically significant (RR, 0.30; P = .13). CONCLUSIONS This analysis suggests that using metformin in patients treated with AAPs may reduce metabolic risks. Additional randomized controlled trials are needed, but available data support consideration of this intervention in clinical practice.

A Comparison of Adequately vs. Inadequately Treated Depressed Patients

The authors reviewed the records of 201 nonbipolar depressed inpatients to a) determine the level of somatic therapies prescribed and b) compare the characteristics and global outcomes of patients given “adequate” vs. “inadequate” treatment. A stepwise multiple regression analysis revealed that patients given higher levels of somatic therapy were significantly (p<.001) more likely to be older and have depression with psychotic features and less likely to have compulsive personality disorders. These patients also had significantly longer hospitalizations. A separate stepwise regression analysis showed that patients given higher levels of somatic therapy had superior outcomes (p<.001). The proportion of this sample given no antidepressant medication or electroconvulsive therapy (18.4%) and the proportion given “adequate” treatment (45.3% to 63.7%, depending on the criteria applied) were comparable to the findings of other published reports.

Length of psychiatric hospitalization is correlated with CYP2D6 functional status in inpatients with major depressive disorder.

AIM This study aimed to determine the effect of the CYP2D6 genotype on the length of hospitalization stay for patients treated for major depressive disorder. METHODS A total of 149 inpatients with a diagnosis of major depressive disorder at the Institute of Living, Hartford Hospital (CT, USA), were genotyped to detect altered alleles in the CYP2D6 gene. Prospectively defined drug metabolism indices (metabolic reserve, metabolic alteration and allele alteration) were determined quantitatively and assessed for their relationship to length of hospitalization stay. RESULTS Hospital stay was significantly longer in deficient CYP2D6 metabolizers (metabolic reserve <2) compared with functional or suprafunctional metabolizers (metabolic reserve ≥2; 7.8 vs 5.7 days, respectively; p = 0.002). CONCLUSION CYP2D6 enzymatic functional status significantly affected length of hospital stay, perhaps due to reduced efficacy or increased side effects of the medications metabolized by the CYP2D6 isoenzyme. Functional scoring of CYP2D6 alleles may have a substantial impact on the quality of care, patient satisfaction and the economics of psychiatric treatment.

Functional impairment in depressed inpatients

The Sickness Impact Profile (SIP) was administered to 95 patients with major depression. The SIP includes 12 subscales, each representing a specific area of sickness-related dysfunction. To relate these measures to psychiatric symptoms, patients also completed a measure of depression severity. Consistent with earlier findings, there were high levels of functional impairment. Impairment was correlated with symptoms but, as noted elsewhere, functional status does not always parallel symptom severity. The SIP, widely used with medical disorders but, to our knowledge, underutilized to assess psychiatric patients, may provide more precise assessment of the impact of psychiatric disorders on the individuals daily life.

Last-Observation-Carried-Forward Imputation Method in Clinical Efficacy Trials: Review of 352 Antidepressant Studies

Study Objective. To determine the prevalence, over 40 years, of using the last‐observation‐carried‐forward (LOCF) imputation method in clinical trials, the association between use of LOCF and how the trials were conducted, and the extent of information about attrition and LOCF use in published reports.

Novel drug metabolism indices for pharmacogenetic functional status based on combinatory genotyping of CYP2C9, CYP2C19 and CYP2D6 genes.

AIMS We aim to demonstrate clinical relevance and utility of four novel drug-metabolism indices derived from a combinatory (multigene) approach to CYP2C9, CYP2C19 and CYP2D6 allele scoring. Each index considers all three genes as complementary components of a liver enzyme drug metabolism system and uniquely benchmarks innate hepatic drug metabolism reserve or alteration through CYP450 combinatory genotype scores. METHODS A total of 1199 psychiatric referrals were genotyped for polymorphisms in the CYP2C9, CYP2C19 and CYP2D6 gene loci and were scored on each of the four indices. The data were used to create distributions and rankings of innate drug metabolism capacity to which individuals can be compared. Drug-specific indices are a combination of the drug metabolism indices with substrate-specific coefficients. RESULTS The combinatory drug metabolism indices proved useful in positioning individuals relative to a population with regard to innate drug metabolism capacity prior to pharmacotherapy. Drug-specific indices generate pharmacogenetic guidance of immediate clinical relevance, and can be further modified to incorporate covariates in particular clinical cases. CONCLUSIONS We believe that this combinatory approach represents an improvement over the current gene-by-gene reporting by providing greater scope while still allowing for the resolution of a single-gene index when needed. This method will result in novel clinical and research applications, facilitating the translation from pharmacogenomics to personalized medicine, particularly in psychiatry where many drugs are metabolized or activated by multiple CYP450 isoenzymes.