Practice effects in healthy adults: a longitudinal study on frequent repetitive cognitive testing.

BACKGROUND: Cognitive deterioration is a core symptom of many neuropsychiatric disorders and target of increasing significance for novel treatment strategies. Hence, its reliable capture in long-term follow-up studies is prerequisite for recording the natural course of diseases and for estimating potential benefits of therapeutic interventions. Since repeated neuropsychological testing is required for respective longitudinal study designs, occurrence, time pattern and magnitude of practice effects on cognition have to be understood first under healthy good-performance conditions to enable design optimization and result interpretation in disease trials. METHODS: Healthy adults (N = 36; 47.3 ± 12.0 years; mean IQ 127.0 ± 14.1; 58% males) completed 7 testing sessions, distributed asymmetrically from high to low frequency, over 1 year (baseline, weeks 2-3, 6, 9, months 3, 6, 12). The neuropsychological test battery covered 6 major cognitive domains by several well-established tests each. RESULTS: Most tests exhibited a similar pattern upon repetition: (1) Clinically relevant practice effects during high-frequency testing until month 3 (Cohen's d 0.36-1.19), most pronounced early on, and (2) a performance plateau thereafter upon low-frequency testing. Few tests were non-susceptible to practice or limited by ceiling effects. Influence of confounding variables (age, IQ, personality) was minor. CONCLUSIONS: Practice effects are prominent particularly in the early phase of high-frequency repetitive cognitive testing of healthy well-performing subjects. An optimal combination and timing of tests, as extractable from this study, will aid in controlling their impact. Moreover, normative data for serial testing may now be collected to assess normal learning curves as important comparative readout of pathological cognitive processes.

The cross-sectional GRAS sample: a comprehensive phenotypical data collection of schizophrenic patients.

BACKGROUND: Schizophrenia is the collective term for an exclusively clinically diagnosed, heterogeneous group of mental disorders with still obscure biological roots. Based on the assumption that valuable information about relevant genetic and environmental disease mechanisms can be obtained by association studies on patient cohorts of ≥ 1000 patients, if performed on detailed clinical datasets and quantifiable biological readouts, we generated a new schizophrenia data base, the GRAS (Göttingen Research Association for Schizophrenia) data collection. GRAS is the necessary ground to study genetic causes of the schizophrenic phenotype in a 'phenotype-based genetic association study' (PGAS). This approach is different from and complementary to the genome-wide association studies (GWAS) on schizophrenia. METHODS: For this purpose, 1085 patients were recruited between 2005 and 2010 by an invariable team of traveling investigators in a cross-sectional field study that comprised 23 German psychiatric hospitals. Additionally, chart records and discharge letters of all patients were collected. RESULTS: The corresponding dataset extracted and presented in form of an overview here, comprises biographic information, disease history, medication including side effects, and results of comprehensive cross-sectional psychopathological, neuropsychological, and neurological examinations. With >3000 data points per schizophrenic subject, this data base of living patients, who are also accessible for follow-up studies, provides a wide-ranging and standardized phenotype characterization of as yet unprecedented detail. CONCLUSIONS: The GRAS data base will serve as prerequisite for PGAS, a novel approach to better understanding 'the schizophrenias' through exploring the contribution of genetic variation to the schizophrenic phenotypes.

Prediction of the risk of comorbid alcoholism in schizophrenia by interaction of common genetic variants in the corticotropin-releasing factor system.

CONTEXT: Stress plays a major role in the development of comorbid alcohol use disorder (AUD). In turn, AUD worsens the outcome of psychiatric patients with respect to global disease severity, social situation, and socioeconomic burden. Prediction of persons at risk for AUD is crucial for future preventive and therapeutic strategies. OBJECTIVE: To investigate whether genetic variants of the corticotropin-releasing factor system or their interaction influence the risk of developing AUD in chronic disease populations. DESIGN: Genotype analysis comprising selected single-nucleotide polymorphisms within the CRHR1 and CRHBP genes in patients with schizophrenia and in a nonschizophrenic psychiatric disease control sample should allow the extraction of predictors of comorbid AUD. Gene expression (messenger RNA) analysis in peripheral blood mononuclear cells was performed to gain the first mechanistic insight. SETTING: An ideal setup for this study was the Göttingen Research Association for Schizophrenia Data Collection of schizophrenic patients, specifically intended to enable association of genetic information with quantifiable phenotypes in a phenotype-based genetic association study. Patients  A total of 1037 schizophrenic patients (Göttingen Research Association for Schizophrenia sample), 80 nonschizophrenic psychiatric disease controls as a small replicate sample, and a case-control study including 1141 healthy subjects. MAIN OUTCOME MEASURES: Association of CRHR1 and CRHBP genotypes with the following: (1) AUD; (2) a newly developed alcoholism severity score comprising 5 AUD-relevant variables; and (3) quantitative CRHR1 and CRHBP messenger RNA expression. RESULTS: An interaction of CRHR1 rs110402 and CRHBP rs3811939 predicts high risk of comorbid AUD in schizophrenic patients (odds ratio = 2.27; 95% confidence interval, 1.56-3.30; P < .001) as well as psychiatric disease controls (odds ratio = 4.02; 95% confidence interval, 0.95-17.05; P = .06) and leads to the highest CRHR1/CRHBP messenger RNA ratio (P = .02; dysbalanced stress axis). CONCLUSIONS: The high predictive value of a genetic interaction within the stress axis for the risk of comorbid AUD may be used for novel preventive and individualized therapeutic approaches.