Natalya S. Weber

Validation of a Blood-Based Laboratory Test to Aid in the Confirmation of a Diagnosis of Schizophrenia

We describe the validation of a serum-based test developed by Rules-Based Medicine which can be used to help confirm the diagnosis of schizophrenia. In preliminary studies using multiplex immunoassay profiling technology, we identified a disease signature comprised of 51 analytes which could distinguish schizophrenia (n = 250) from control (n = 230) subjects. In the next stage, these analytes were developed as a refined 51-plex immunoassay panel for validation using a large independent cohort of schizophrenia (n = 577) and control (n = 229) subjects. The resulting test yielded an overall sensitivity of 83% and specificity of 83% with a receiver operating characteristic area under the curve (ROC-AUC) of 89%. These 51 immunoassays and the associated decision rule delivered a sensitive and specific prediction for the presence of schizophrenia in patients compared to matched healthy controls.

Development of a blood-based molecular biomarker test for identification of schizophrenia before disease onset.

Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95–1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86–0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71–0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82–0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset.

Identification of a blood-based biological signature in subjects with psychiatric disorders prior to clinical manifestation

Abstract Objectives. To determine whether a molecular signature is present in blood of patients with psychiatric disorders before manifestation of symptoms. Methods. Multiplex immunoassay analyses were carried out using serum obtained from two case-control studies of schizophrenia (n = 75) and bipolar disorder (n = 110) patients and their matched controls. The samples were drawn within 1 month before estimated onset of illness. Results. This led to identification of 20 molecules which were altered in pre-schizophrenia and 14 molecules in pre-bipolar disorder subjects compared to controls. Only two of these molecular changes were identical in both data sets and predictive testing confirmed that the biomarker signatures for pre-schizophrenia and pre-bipolar disorder were dissimilar. Conclusion. The present results suggest that there are distinct serum alterations that occur before clinical manifestation of schizophrenia and bipolar disorder. These findings could lead to development of diagnostic tests to help clinical psychiatrists identify and classify vulnerable patients early in the disease process, allowing for earlier and more effective therapeutic intervention.

Psychiatric and General Medical Conditions Comorbid With Bipolar Disorder in the National Hospital Discharge Survey

OBJECTIVE From 40% to 65% of patients with bipolar disorder are estimated to have diagnoses of one or more comorbid conditions. The purpose of this study was to identify comorbid disorders and compare their prevalence in hospitalizations of persons with or without bipolar disorder. METHODS Data from the 1979-2006 National Hospital Discharge Survey (NHDS) were analyzed to examine temporal trends in the proportional morbidity of bipolar disorder, demographic characteristics, and the most frequent comorbid conditions in hospitalizations of patients with or without bipolar disorder. Among discharges of patients ages 13-64, the conditions of those with a primary diagnosis of bipolar disorder (N=27,054) were compared with those with other primary diagnoses (N=2,325,247). Proportional morbidity ratios (PMRs) were calculated. RESULTS There was an average 10% (p<.001) increase per year in the proportion of discharges with bipolar disorder. Proportions of discharge records that noted bipolar disorder were higher among females and whites and were highest among persons ages 13-19 and those from the Northeast. Discharge records noting a primary diagnosis of bipolar disorder showed higher proportions of most psychiatric and some general medical conditions, including acquired hypothyroidism (proportional morbidity ratio=2.6), viral hepatitis (1.6), obesity (1.4), and various diseases of the skin and subcutaneous tissue (range 2.6-4.2) and of the nervous (1.4-3.8), respiratory (1.4-2.3), and musculoskeletal (1.2-1.9) systems. CONCLUSIONS Patients with bipolar disorder have an increased illness burden from many psychiatric and general medical conditions. Knowledge of the most prevalent comorbid conditions and methods for their prevention, early diagnosis, and treatment are critical in improving the prognosis of patients with bipolar disorder.

Towards a blood-based diagnostic panel for bipolar disorder

BACKGROUND Bipolar disorder (BD) is a costly, devastating and life shortening mental disorder that is often misdiagnosed, especially on initial presentation. Misdiagnosis frequently results in ineffective treatment. We investigated the utility of a biomarker panel as a diagnostic test for BD. METHODS AND FINDINGS We performed a meta-analysis of eight case-control studies to define a diagnostic biomarker panel for BD. After validating the panel on established BD patients, we applied it to undiagnosed BD patients. We analysed 249 BD, 122 pre-diagnostic BD, 75 pre-diagnostic schizophrenia and 90 first onset major depression disorder (MDD) patients and 371 controls. The biomarker panel was identified using ten-fold cross-validation with lasso regression applied to the 87 analytes available across the meta-analysis studies. We identified 20 protein analytes with excellent predictive performance [area under the curve (AUC)⩾0.90]. Importantly, the panel had a good predictive performance (AUC 0.84) to differentiate 12 misdiagnosed BD patients from 90 first onset MDD patients, and a fair to good predictive performance (AUC 0.79) to differentiate between 110 pre-diagnostic BD patients and 184 controls. We also demonstrated the disease specificity of the panel. CONCLUSIONS An early and accurate diagnosis has the potential to delay or even prevent the onset of BD. This study demonstrates the potential utility of a biomarker panel as a diagnostic test for BD.

Association between antibodies to multiple infectious and food antigens and new onset schizophrenia among US military personnel

INTRODUCTION Multiple studies have documented immune activation in many individuals with schizophrenia suggesting that antigens capable of generating a prolonged immune response may be important environmental factors in many cases of this disorder. While existing studies have found single-agent associations of antibodies to food and neurotropic infectious agents with schizophrenia, a simultaneous examination of multiple agents may shed light on agent interactions or possible etiopathogenic pathways. METHODS We used traditional regression and novel statistical techniques to examine associations of single and combined infectious and food antigens with schizophrenia. We tested 6106 serum samples from 855 cases and 1165 matched controls. RESULTS Higher antibody levels to casein were borderline significant in the prediction of schizophrenia (HR=1.08, p=0.06). Study participants with higher cytomegalovirus (CMV) IgG antibody levels had a reduced risk of developing schizophrenia (HR=0.90; p=0.02). While IgG antibodies to gliadin, Toxoplasma gondii, vaccinia, measles, and human herpesvirus-6 (HHV-6) showed no significant independent associations with schizophrenia, the increase in antibody levels to several combinations of agents, to include casein, measles, CMV, T. gondii and vaccinia, was predictive of an 18-34% increase in the risk of developing schizophrenia. CONCLUSION Certain patterns of antibodies, involving some agents, were predictive of developing schizophrenia, with the magnitude of association rising when the level of antibodies increased to two or more agents. A heightened antibody response to a combination of several infectious/food antigens might be an indicator of an altered immune response to antigenic stimuli.

Evaluation of Data Obtained from Military Disability Medical Administrative Databases for Service Members with Schizophrenia or Bipolar Disorder

OBJECTIVE We are studying associations between selected biomarkers and schizophrenia or bipolar disorder among military personnel. To assess potential diagnostic misclassification and to estimate the date of illness onset, we reviewed medical records for a subset of cases. METHODS Two psychiatrists independently reviewed 182 service medical records retrieved from the Department of Veterans Affairs. Data were evaluated for diagnostic concordance between database diagnoses and reviewers. Interreviewer variability was measured by using proportion of agreement and the kappa statistic. Data were abstracted to estimate date of onset. RESULTS High levels of agreement existed between database diagnoses and reviewers (proportion, 94.7%; kappa = 0.88) and between reviewers (proportion, 92.3%; kappa = 0.87). The median time between illness onset and initiation of medical discharge was 1.6 and 1.1 years for schizophrenia and bipolar disorder, respectively. CONCLUSIONS High levels of agreement between investigators and database diagnoses indicate that diagnostic misclassification is unlikely. Discharge procedure initiation date provides a suitable surrogate for disease onset.

Incidence of adult onset schizophrenic disorders in the US Military: Patterns by sex, race and age

BACKGROUND There are limited data describing the epidemiology of adult-onset schizophrenic disorders in the United States. Although the military is not proportionately comparable in all demographic characteristics to the civilian population, it is drawn from all racial/ethnic subgroups, and members range in age from 17 to >60 years. We describe the incidence of hospitalization for new onset schizophrenic disorders among military members by sex, race, and age. METHODS Using military inpatient data, we evaluated patterns of initial hospitalizations for schizophrenic disorders among military personnel for 2000-2009, focusing on sex, race, and age. No individual-level data were available. RESULTS From 2000-2009, 1976 military personnel had a first schizophrenic disorder hospitalization, with an overall incidence rate of 0.14/1000 person-years. There were no consistent changes in rates over time. While overall incidence rates were similar for men and women (incidence rate ratio (IRR)=1.10), rates were higher among men than women below age 25; after 25-30 rates were higher among women. Incidence was higher among blacks and other racial groups, with IRR=2.0 and 1.3, respectively. CONCLUSION Medical screening of military applicants prevents persons with overt or a reported history of psychosis, and most with serious behavior problems, from enlisting; therefore, first hospitalization is likely to reflect new illness. No pre-military socioeconomic data were available, however, essentially all study subjects were high school graduates; unmeasured differences in socioeconomic status were unlikely to explain the observed results. This report may provide lower bound estimates of the schizophrenic disorder incidence in the United States.

Personality Assessment Questionnaire as a pre-accession screen for risk of mental disorders and early attrition in U. S. Army recruits.

Personality assessment tools have been studied as predictors of performance in civilian and military work settings. The Tailored Adaptive Personality Assessment System (TAPAS) was developed to improve selection of new military recruits by predicting motivational outcomes such as job effort, physical fitness, and drive to perform at high standards. The purpose of this study is to examine the utility of TAPAS as a predictor of psychiatric morbidity and early discharge in a sample of 15,082 Army, active duty, enlisted, nonprior service recruits. Associations between TAPAS personality dimension score quintiles and mental disorder diagnoses, attrition, and health care utilization in United States Army recruits who took TAPAS in the fiscal year 2010 were analyzed using multivariate logistic regression and log-linear modeling. TAPAS physical conditioning dimension scores were predictive of mental disorder diagnosis and attrition, with TAPAS scorers in the lowest quintile at increased odds of early discharge (odds ratio [OR]: 2.08, 95% CI 1.73, 2.51), mental disorder diagnosis (OR: 1.41, 95% CI 1.20, 1.66) and greater mental health care utilization (1.61, 95% CI 1.46, 1.78) compared with TAPAS scorers in the highest quintile. Results indicated that TAPAS may have an important use as a mental health fitness screening tool for those who wish to serve in the military by identifying a limited high risk group of applicants for mental health diagnostic evaluation. TAPAS may augment current cognitive and educational screens and potentially reduce the burden of mental disorders and premature attrition.

Descriptive Epidemiology and Underlying Psychiatric Disorders among Hospitalizations with Self-Directed Violence

Background Suicide claims over one million lives worldwide each year. In the United States, 1 per 10,000 persons dies from suicide every year, and these rates have remained relatively constant over the last 20 years. There are nearly 25 suicide attempts for each suicide, and previous self-directed violence is a strong predictor of death from suicide. While many studies have focused on suicides, the epidemiology of non-fatal self-directed violence is not well-defined. Objective We used a nationally representative survey to examine demographics and underlying psychiatric disorders in United States (US) hospitalizations with non-fatal self-directed violence (SDV). Method International Classification of Disease, 9th Revision (ICD-9) discharge diagnosis data from the National Hospital Discharge Survey (NHDS) were examined from 1997 to 2006 using frequency measures and adjusted logistic regression. Results The rate of discharges with SDV remained relatively stable over the study time period with 4.5 to 5.7 hospitalizations per 10,000 persons per year. Excess SDV was documented for females, adolescents, whites, and those from the Midwest or West. While females had a higher likelihood of self-poisoning, both genders had comparable proportions of hospitalizations with SDV resulting in injury. Over 86% of the records listing SDV also included psychiatric disorders, with the most frequent being affective (57.8%) and substance abuse (37.1%) disorders. The association between psychiatric disorders and self-injury was strongest for personality disorders for both males (OR = 2.1; 95% CI = 1.3–3.4) and females (OR = 3.8; 95% CI = 2.7–5.3). Conclusion The NHDS provides new insights into the demographics and psychiatric morbidity of those hospitalized with SDV. Classification of SDV as self-injury or self-poisoning provides an additional parameter useful to epidemiologic studies.