Understanding Aging in Bipolar Disorder by Integrating Archival Clinical Research Datasets.

OBJECTIVE: Although 25% of people with bipolar disorder (BD) are over age 60, there is a dearth of research on older age bipolar disorder (OABD). This report describes an initial effort to create an integrated OABD database using the U.S. National Institute of Mental Health Data Archive (NDA). Goals were to: 1) combine data from three BD studies in the United States that included overlapping data elements; 2) investigate research questions related to aims of the original studies; and 3) take an important first step toward combining existing datasets relevant to aging and BD. METHODS: Data were prepared and uploaded to the NDA, with a focus on data elements common to all studies. As appropriate, data were harmonized to select or collapse categories suitable for cross-walk analysis. Associations between age, BD symptoms, functioning, medication load, medication adherence, and medical comorbidities were assessed. The total sample comprised 451 individuals, mean age 57.7 (standard deviation: 13.1) years. RESULTS: Medical comorbidity was not significantly associated with either age or functioning and there did not appear to be an association between medication load, comorbidity, age, and adherence. Men and African-Americans were significantly more likely to have poor adherence. Both BD mania and depression symptoms were associated with functioning, but this differed across studies. CONCLUSION: Despite limitations including heterogeneity in study design and samples and cross-sectional methodology, integrated datasets represent an opportunity to better understand how aging may impact the presentation and evolution of chronic mental health disorders across the lifespan.

Psychometric Evaluation of the National Institutes of Health Patient-Reported Outcomes Measurement Information System in a Multiracial, Multiethnic Systemic Lupus Erythematosus Cohort.

OBJECTIVE: We examined psychometric performance of Patient-Reported Outcomes Measurement Information System (PROMIS) measures in a racially/ethnically and linguistically diverse cohort with systemic lupus erythematosus (SLE). METHODS: Data were from the California Lupus Epidemiology Study, a multiracial/multiethnic cohort of individuals with physician-confirmed SLE. The majority (n = 332) attended in-person research visits that included interviews conducted in English, Spanish, Cantonese, or Mandarin. Up to 12 PROMIS short forms were administered (depending on language availability). An additional 99 individuals completed the interview by phone only. Internal consistency was examined with Cronbach's alpha and item-total correlations. Correlations with the Short Form 36 subscales and both self-reported and physician-assessed disease activity assessed convergent validity. All analyses were repeated within each racial/ethnic group. Differences in scores by race/ethnicity were examined in bivariate analyses and by multiple regression analyses controlling for age, sex, disease duration, and disease damage and activity. RESULTS: The total sample was 30.0% white, 22.3% Hispanic, 10.9% African American, 33.7% Asian, and 3.0% other race/ethnicity. Seventy-seven percent of interviews were conducted in-person. Non-English interviews were conducted in 26.0% of the Hispanic subjects and 18.6% of the Asian subjects. Each scale demonstrated adequate reliability and validity overall and within racial/ethnic groups. Minimal floor effects were observed, but ceiling effects were noted. Missing item responses were minimal for most scales, except for items related to work. No differences were noted by mode of administration or by language of administration among Hispanics and Asians. After accounting for differences in disease status, age, and sex, few differences in mean scores between whites and other racial/ethnic groups were noted. CONCLUSION: PROMIS measures appear reliable and valid in persons with lupus across racial/ethnic groups.

Asignaturas pendientes del DSM-5 / Unresolved issues in the DSM-5

el presente artículo analiza las críticas generadas a partir de la publicación del Manual diagnóstico y estadístico de los trastornos mentales, quinta edición (DSM-5), ya anunciadas parcialmente durante las últimas fases de su elaboración. Una parte de las críticas se ha centrado en los cambios de los criterios diagnósticos para determinados trastornos y en la incorporación al DSM de nuevas entidades. Sin embargo, otra vertiente crítica va dirigida a la falta de validez de los diagnósticos del DSM, por cuyo motivo se ha cuestionado su eficiencia en el campo de la investigación. El fallo básico del DSM se centra en la incoherencia de un modelo basado en un amplio repertorio de definiciones de entidades categóricas, todas ellas con un alto componente de comorbilidad. Como propuesta para superar el bloqueo generado en la investigación y la parquedad de avances terapéuticos, el Instituto Nacional de Salud Mental de Estados Unidos ha propuesto una estrategia de investigación cuyo punto de partida se sustenta en la identificación y el estudio de las dimensiones básicas de las disfunciones que se presentan de modo transversal en los trastornos mentales (AU)

This paper analyses the criticism prompted by the publication of the Diagnostic and statistical manual of mental disorders, fifth edition (DSM-5), which was already foreseen to a certain extent during the final stages of its drafting. Part of the criticism has focused on the changes in the diagnostic criteria for certain disorders and the incorporation of new entities into the DSM. Another line of criticism, however, is aimed at the lack of diagnostic validity of the DSM, which has led to its efficiency in the research field being questioned. The basic underlying flaw in the DSM is the incoherence of a model based on a wide range of definitions of categorical entities, all of which have a high element of comorbidity. As a proposal to overcome the blockage generated in research and the scarcity of therapeutic advances, the US National Institute of Mental Health has put forward a research strategy based on identifying and studying the fundamental dimensions of the dysfunctions that present transversally in mental disorders (AU)

Meta-analysis of repository data: impact of data regularization on NIMH schizophrenia linkage results.

Human geneticists are increasingly turning to study designs based on very large sample sizes to overcome difficulties in studying complex disorders. This in turn almost always requires multi-site data collection and processing of data through centralized repositories. While such repositories offer many advantages, including the ability to return to previously collected data to apply new analytic techniques, they also have some limitations. To illustrate, we reviewed data from seven older schizophrenia studies available from the NIMH-funded Center for Collaborative Genomic Studies on Mental Disorders, also known as the Human Genetics Initiative (HGI), and assessed the impact of data cleaning and regularization on linkage analyses. Extensive data regularization protocols were developed and applied to both genotypic and phenotypic data. Genome-wide nonparametric linkage (NPL) statistics were computed for each study, over various stages of data processing. To assess the impact of data processing on aggregate results, Genome-Scan Meta-Analysis (GSMA) was performed. Examples of increased, reduced and shifted linkage peaks were found when comparing linkage results based on original HGI data to results using post-processed data within the same set of pedigrees. Interestingly, reducing the number of affected individuals tended to increase rather than decrease linkage peaks. But most importantly, while the effects of data regularization within individual data sets were small, GSMA applied to the data in aggregate yielded a substantially different picture after data regularization. These results have implications for analyses based on other types of data (e.g., case-control GWAS or sequencing data) as well as data obtained from other repositories.

Diagnosis of schizophrenia: consistency across information sources and stability of the condition.

BACKGROUND: The Social Security Administration is considering whether schizophrenia may warrant inclusion in their new "Compassionate Allowance" process, which aims to identify diseases and other medical conditions that almost always qualify for Social Security disability benefits simply on the basis of their confirmed presence. This paper examines the reliability and validity of schizophrenia diagnosis, how a valid diagnosis is established, and the stability of the diagnosis over time. A companion paper summarizes evidence on the empirical association between schizophrenia and disability, thus leading to this paper that evaluates how valid clinical diagnoses of schizophrenia are. METHODS: Literature review and synthesis, based on a workplan developed in an expert meeting convened by the National Institute of Mental Health and the Social Security Administration. FINDINGS: At least since the introduction of the 3rd edition of the American Psychiatric Association's Diagnostic and Statistical Manual (DSM-III) in 1980, diagnoses of schizophrenia made by mental health specialists are valid, reliable, and stable over time, across community as well as academic practice settings, and across different assessment methods. These analyses are particularly valid during the time-frame relevant to social security awards: at least 2 years after the initial stages of illness. We could not find studies that have evaluated the validity or reliability of schizophrenia diagnoses made exclusively by primary care providers (vs. mental health professionals). DISCUSSION: In the post-DSM-III era, schizophrenia diagnosis-using modern diagnostic criteria-is valid and reliable when performed by doctoral-level mental health specialists (i.e., psychiatrists and psychologists), in community as well as academic settings.

Evaluation of psychiatric interventions in an observational study: issues in design and analysis.

Characteristics of randomized controlled clinical trials (RCTs) and observational studies of psychiatric intervention effectiveness are contrasted. Randomization drives treatment assignment in an RCT, whereas clinician and patient selection determine treatment in an observational study. Strengths and weaknesses of randomized and observational designs are considered. The propensity adjustment, a statistical approach that allows for intervention evaluation in a nonrandomized observational study, is described here. The plausibility of propensity adjustment assumptions must be carefully evaluated. This data analytic strategy is illustrated with the longitudinal observational data from the National Institute of Mental Health Collaborative Depression Study. Evaluations presented here examine acute and maintenance antidepressant effectiveness and demonstrate effectiveness of the higher categorical doses.

Genetic repositories for the study of major psychiatric conditions: what do we know about ethnic minorities' genetic vulnerability?

In spite of considerable efforts, no genes of major effect have been found across an entire diagnostic category in psychiatry. Possible reasons for this may include difficulties in defining the phenotype, the complex relationship between genotype and gene expression and population stratification. This last problem has often been managed by restricting genetic sampling to only one ethnic group. An unintended consequence of using this strategy is that the major repositories of genetic material for the study of psychiatric conditions in the United States suffer from a paucity of genetic samples from non-Caucasian groups. Thus, these groups are being relatively understudied in terms of the genetic antecedents to psychiatric disease. The authors provide solutions including the need to augment the representation of African-American, Latino and Asian-Americans among research participants; a more nuanced approach to identify ancestry; and the development of analytic and genetic strategies to handle the issue of ethnic heterogeneity in samples.

A comparison between screened NIMH and clinically interviewed control samples on neuroticism and extraversion.

The National Institute of Mental Health (NIMH) has supported the collection of DNA samples on over 4000 subjects for use primarily as controls in psychiatric genetic studies. These subjects, though screened online, were not directly interviewed or assessed on family history. We compared this sample to one that was directly interviewed using structured diagnostic assessments on comparable measures of neuroticism and extraversion. The screened sample completed an online self-report based on the Composite International Diagnostic Instrument Short-Form (CIDI-SF). The interviewed sample was assessed by clinically trained personnel using the Schedule for Affective Disorders and Schizophrenia (SADS-LA-IV) and Family History Screen; final diagnoses were made blind to trait scores by a clinician using the best-estimate procedure. Neuroticism and extraversion were assessed on the NEO five-factor inventory (NEO-FFI) and the revised Eysenck Personality Questionnaire short form (EPQ-R). We found that subjects in the NIMH-screened sample who did not report any psychiatric symptoms on the self-report were indistinguishable from interviewed diagnosis free and family history negative controls on neuroticism and extraversion. Subjects in the screened sample who screened positive for anxiety disorders, however, deviated significantly on these measures both from the screened subjects with no self-reported symptoms, as well as from subjects in the interviewed sample diagnosed with comparable disorders. These findings suggest that control groups generated from the NIMH sample should ideally be restricted to subjects free of any self-reported symptoms, regardless of the disorder being addressed, in order to maximize their reflection of diagnosis-free populations.