Currently utilized clinician-rated symptom scales for tardive dyskinesia (TD) have not kept up with the expanding spectrum of TD phenomenology. The objective of this study was to develop and test the reliability of a new instrument, the CTI.

A movement disorder neurologist devised the outline of the scale. A steering committee (four neurologists and two psychiatrists) provided revisions until consensus was reached. The resulting instrument assesses frequency of abnormal movements of the eye/eyelid/face, tongue/mouth, jaw, limb/trunk, complex movements (e.g., handwringing, self-caressing), and vocalizations. The CTI rates symptoms from 0–3 with 0 = absent, 1 = infrequent/intermittent or only present with activating maneuvers, 2 = frequent intermittent, brief periods without movements, 3 = constant or nearly constant. Functional impairments including activities of daily living (ADL), social impairment, symptom bother, and harm are rated 0–3 with 0 = patient is unaware or unaffected, 1 = symptoms mildly impact patient, 2 = symptoms moderately impact patient, 3 = symptoms severely impact patient. Following institutional review board approval, the CTI underwent inter-rater and test-retest reliability testing. Videos of patient TD examinations were obtained and reviewed by two movement disorder specialists to confirm the diagnosis of TD by consensus and the adequacy to demonstrate a TD-consistent movement. Vignettes were created to include patients’ symptom descriptions and functional, social, or occupational impairments/limitations. Four clinicians rated each video/vignette. Selected videos/vignettes were also subject to an intra-rater retest. Interrater agreement was analyzed via 2-way random-effects interclass correlation (ICC) and test-retest agreement assessment utilizing Kendall’s tau-b.

45 video/vignettes were assessed for interrater reliability, and 16 for test-retest reliability. ICCs for movement frequency were as follows: abnormal eye movement .89; abnormal tongue/mouth movement .91; abnormal jaw movement .89; abnormal limb movement .76; complex movement .87; abnormal vocalization .77; and functional impairments including harm .82; social embarrassment .88; ADLs .83; and symptom bother .92. Retests were conducted on mean (SD) 15 (3) days later with scores ranging from .66–.87.

The CTI is a new instrument with good reliability in assessing TD symptoms and functional impacts. Future validation study is warranted.

Neurocrine Biosciences

Psychiatric hospitalization is a major driver of cost in the treatment of schizophrenia. Here, we asked whether a technology-enhanced approach to relapse prevention could reduce days spent in a hospital after discharge.

The Improving Care and Reducing Cost (ICRC) study was a quasi-experimental clinical trial in outpatients with schizophrenia conducted between 26 February 2013 and 17 April 2015 at 10 different sites in the USA in an outpatient setting. Patients were between 18 and 60 years old with a diagnosis of schizophrenia, schizoaffective disorder, or psychotic disorder not otherwise specified. Patients received usual care or a technology-enhanced relapse prevention program during a 6-month period after discharge. The health technology program included in-person, individualized relapse prevention planning with treatments delivered via smartphones and computers, as well as a web-based prescriber decision support program. The main outcome measure was days spent in a psychiatric hospital during 6 months after discharge.

The study included 462 patients, of which 438 had complete baseline data and were thus used for propensity matching and analysis. Control participants (N = 89; 37 females) were enrolled first and received usual care for relapse prevention followed by 349 participants (128 females) who received technology-enhanced relapse prevention. During 6-month follow-up, 43% of control and 24% of intervention participants were hospitalized (χ2 = 11.76, p<0.001). Days of hospitalization were reduced by 5 days (mean days: b = −4.58, 95% CI −9.03 to −0.13, p = 0.044) in the intervention condition compared to control.

These results suggest that technology-enhanced relapse prevention is an effective and feasible way to reduce rehospitalization days among patients with schizophrenia.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

In two recent studies the SNP rs2230912 (Gln460Arg) located in exon 13 of P2RX7-gene (chromosome 12q24) provided the strongest evidence of association with bipolar disorder (BP) (Barden et al,2006; McQuillin et al, 2008) and in one study with the unipolar major depression (Mdd-UP) ( Lucae et al, 2006).

In the present study we investigated the involvement of the SNP rs2230912 in BPI in four European samples from Germany, Poland, Romania and Russia and in the combined sample (N=1445) in comparison with a combined sample of 2006 normal controls. Additionally, a Mdd-UP sample (N=640) from Germany was studied.

All patients were diagnosed according to DSM-IV-R. The BPI sample consisted of 802 females (55.5%) and 643 males (44.5%); the mean AO was 26.9 (SD=10.6); the mean age-at-interview was 42.7 (SD=12.5). The control sample had a mean age of 39.74 (SD=11.22) [1113 females (55.5%); 893 males (44.5%)]. Genotyping of all national samples was performed at Bonn University using the Mass ARRAY system on a Sequenom Compact MALDI-TOF-device. The single marker analysis was performed with FAMHAP software.

There was no allelic association between the G-allele of the SNP rs2230912 and either BPI or Mdd-UP both in the national samples and in the combined sample. The genotypic analysis also indicated no significant results. Our samples of patients and controls had genotypic distributions similar to those of the previously published studies and even in these studies there were no significant differences in genotype frequencies between BPI patients and controls.

Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability).

For investigating familiality, we used 691 families with 2–5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software.

Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity.

AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.

Hypersensitivity to electromagnetic fields (EMF) is frequently claimed to be linked to a variety of non-specific somatic and neuropsychological complaints. Whereas provocation studies often failed to demonstrate a causal relationship between EMF exposure and symptom formation, recent studies point to a complex interplay of neurophysiological and cognitive alterations contributing to symptom manifestation in electromagnetic hypersensitive patients (EHS). However, these studies have examined only small sample sizes or have focused on selected aspects. Therefore this study examined in the largest sample of EHS EMF-specific cognitive correlates, discrimination ability and neurobiological parameters in order to get further insight into the pathophysiology of electromagnetic hypersensitivity.

In a case-control design 89 EHS and 107 age- and gender-matched controls were included in the study. Health status and EMF-specific cognitions were evaluated using standardized questionnaires. Perception thresholds following single transcranial magnetic stimulation (TMS) pulses to the dorsolateral prefrontal cortex were determined using a standardized blinded measurement protocol. Cortical excitability parameters were measured by TMS.

Discrimination ability was significantly reduced in EHS (only 40% of the EHS but 60% of the controls felt no sensation under sham stimulation during the complete series), whereas the perception thresholds for real magnetic pulses were comparable in both groups (median 21% versus 24% of maximum pulse intensity). Intra-cortical facilitation was decreased in younger and increased in older EHS. In addition, typical EMF-related cognitions (aspects of rumination, symptom intolerance, vulnerability and stabilizing self-esteem) specifically differentiated EHS from their controls.

These results demonstrate significant cognitive and neurobiological alterations pointing to a higher genuine individual vulnerability of electromagnetic hypersensitive patients.

A number of scales are used to estimate the severity of depression. However, differences between self-report and clinician rating, multi-dimensionality and different weighting of individual symptoms in summed scores may affect the validity of measurement. In this study we examined and integrated the psychometric properties of three commonly used rating scales.

The 17-item Hamilton Depression Rating Scale (HAMD-17), the Montgomery–Asberg Depression Rating Scale (MADRS) and the Beck Depression Inventory (BDI) were administered to 660 adult patients with unipolar depression in a multi-centre pharmacogenetic study. Item response theory (IRT) and factor analysis were used to evaluate their psychometric properties and estimate true depression severity, as well as to group items and derive factor scores.

The MADRS and the BDI provide internally consistent but mutually distinct estimates of depression severity. The HAMD-17 is not internally consistent and contains several items less suitable for out-patients. Factor analyses indicated a dominant depression factor. A model comprising three dimensions, namely ‘observed mood and anxiety’, ‘cognitive’ and ‘neurovegetative’, provided a more detailed description of depression severity.

The MADRS and the BDI can be recommended as complementary measures of depression severity. The three factor scores are proposed for external validation.