Precuneus functioning differentiates first-episode psychosis patients during the fantasy movie Alice in Wonderland.

BACKGROUND: While group-level functional alterations have been identified in many brain regions of psychotic patients, multivariate machine-learning methods provide a tool to test whether some of such alterations could be used to differentiate an individual patient. Earlier machine-learning studies have focused on data collected from chronic patients during rest or simple tasks. We set out to unravel brain activation patterns during naturalistic stimulation in first-episode psychosis (FEP). METHOD: We recorded brain activity from 46 FEP patients and 32 control subjects viewing scenes from the fantasy film Alice in Wonderland. Scenes with varying degrees of fantasy were selected based on the distortion of the 'sense of reality' in psychosis. After cleaning the data with a novel maxCorr method, we used machine learning to classify patients and healthy control subjects on the basis of voxel- and time-point patterns. RESULTS: Most (136/194) of the voxels that best classified the groups were clustered in a bilateral region of the precuneus. Classification accuracies were up to 79.5% (p = 5.69 × 10-8), and correct classification was more likely the higher the patient's positive-symptom score. Precuneus functioning was related to the fantasy content of the movie, and the relationship was stronger in control subjects than patients. CONCLUSIONS: These findings are the first to show abnormalities in precuneus functioning during naturalistic information processing in FEP patients. Correlational findings suggest that these alterations are associated with positive psychotic symptoms and processing of fantasy. The results may provide new insights into the neuronal basis of reality distortion in psychosis.

Cortical salience network activation precedes the development of delusion severity.

BACKGROUND: Delusion is the most characteristic symptom of psychosis. While researchers suggested an association between changes of the cortical salience network (CSN) and delusion, whether these CSN findings are a cause or a consequence of delusion remains unknown. METHOD: To assess the effect of CSN functioning to forthcoming changes in delusion scores, we measured brain activation with 3-T functional magnetic resonance imaging in two independent samples of first-episode psychosis patients (total of 27 patients and 23 healthy controls). During scanning, the patients evaluated statements about whether an individual's psychosis-related experiences should be described as a mental illness, and control statements that were also evaluated by healthy controls. Symptoms were assessed at the baseline and at 2 months follow-up with Brief Psychiatric Rating Scale. RESULTS: Both tasks activated the CSN in comparison with rest. Activation of CSN ('illness evaluation v. control task' contrast) in patients positively correlated with worsening of or less improvement in delusions at the 2-month follow-up assessment. This finding was independent of delusion and clinical insight scores at the baseline evaluation. CONCLUSIONS: Our findings link symptom-evaluation-related CSN functioning to severity of delusion and, importantly, add a new layer of evidence for the contribution of CSN functioning to the longitudinal course of delusions.

Association of obesity to reaction time and visual memory in schizophrenia.

Background: Both overweight and cognitive deficits are common among people with schizophrenia (SZ) and schizoaffective disorder. The results in earlier studies have been inconsistent on whether overweight is associated with cognitive deficits in psychotic disorders. Aims: Our aim in this study was to detect possible associations between obesity and cognitive deficits among study participants with SZ and schizoaffective disorder. Methods: The study sample included 5382 participants with a clinical diagnosis of SZ or schizoaffective disorder selected from the Finnish SUPER study. Obesity was measured both with body-mass index and waist circumference. The cognitive performance was evaluated with two tests from the Cambridge automated neuropsychological test battery: Reaction time was evaluated with the 5-choice serial reaction time task. Visual memory was evaluated with the paired associative learning test. The final analysis included a total sample of 4498 participants applicable for the analysis of the reaction time and 3967 participants for the analysis of the visual memory. Results: Obesity measured with body-mass index was associated with better performance in reaction time task among both female and male participants. Among male participants, overweight was associated with better performance in the visual memory test. The waist circumference was not associated with cognitive measures. Conclusions: The results suggest that obesity in people with SZ or schizoaffective disorder might not be associated with cognitive deficits but instead with better cognitive performance. The results were opposite from earlier literature on the general population. More research is required to better understand whether the results might be partly caused by the differences in the etiology of obesity between the general population and people with SZ.

Neuropsychological testing of cognitive impairment in euthymic bipolar disorder: an individual patient data meta-analysis.

OBJECTIVE: An association between bipolar disorder and cognitive impairment has repeatedly been described, even for euthymic patients. Findings are inconsistent both across primary studies and previous meta-analyses. This study reanalysed 31 primary data sets as a single large sample (N = 2876) to provide a more definitive view. METHOD: Individual patient and control data were obtained from original authors for 11 measures from four common neuropsychological tests: California or Rey Verbal Learning Task (VLT), Trail Making Test (TMT), Digit Span and/or Wisconsin Card Sorting Task. RESULTS: Impairments were found for all 11 test-measures in the bipolar group after controlling for age, IQ and gender (Ps ≤ 0.001, E.S. = 0.26-0.63). Residual mood symptoms confound this result but cannot account for the effect sizes found. Impairments also seem unrelated to drug treatment. Some test-measures were weakly correlated with illness severity measures suggesting that some impairments may track illness progression. CONCLUSION: This reanalysis supports VLT, Digit Span and TMT as robust measures of cognitive impairments in bipolar disorder patients. The heterogeneity of some test results explains previous differences in meta-analyses. Better controlling for confounds suggests deficits may be smaller than previously reported but should be tracked longitudinally across illness progression and treatment.

Anti-neuronal anti-bodies in patients with early psychosis.

It may be challenging to distinguish autoimmune encephalitis associated with anti-neuronal autoantibodies from primary psychiatric disorders. Here, serum was drawn from patients with a first-episode psychosis (n=70) or a clinical high-risk for psychosis (n=6) and controls (n=34). We investigated the serum prevalence of 24 anti-neuronal autoantibodies: IgG antibodies for anti-N-methyl-d-aspartate-type glutamate receptor (anti-NMDAR), glutamate and γ-aminobutyric acid alpha and beta receptors (GABA-a, GABA-b), alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPA), glycine receptor (GlyR), metabotropic glutamate receptor 1 and 5 (mGluR1, mGluR5), anti-Tr/Delta/notch-like epidermal growth factor-related receptor (DNER), contactin-associated protein-like 2 (CASPR2), myelin oligodendrocyte glycoprotein (MOG), glutamic acid decarboxylase-65 (GAD65), collapsin response mediator protein 5/crossveinless-2 (CV2), aquaporin-4 (AQP4), anti-dipeptidyl-peptidase-like protein-6 (DPPX), type 1 anti-neuronal nuclear antibody (ANNA-1, Hu), Ri, Yo, IgLON5, Ma2, zinc finger protein 4 (ZIC4), Rho GTPase-activating protein 26, amphiphysin, and recoverin, as well as IgA and IgM for dopamine-2-receptor (DRD2). Anti-NMDA IgG antibodies were positive with serum titer 1:320 in one patient with a clinical high risk for psychosis. He did not receive a diagnosis of encephalitis after comprehensive neurological evaluation. All other antineuronal autoantibodies were negative and there were no additional findings with immunohistochemistry of brain issues.

Serum metabolite profile associates with the development of metabolic co-morbidities in first-episode psychosis.

Psychotic patients are at high risk for developing obesity, metabolic syndrome and type 2 diabetes. These metabolic co-morbidities are hypothesized to be related to both treatment side effects as well as to metabolic changes occurring during the psychosis. Earlier metabolomics studies have shown that blood metabolite levels are predictive of insulin resistance and type 2 diabetes in the general population as well as sensitive to the effects of antipsychotics. In this study, we aimed to identify the metabolite profiles predicting future weight gain and other metabolic abnormalities in psychotic patients. We applied comprehensive metabolomics to investigate serum metabolite profiles in a prospective study setting in 36 first-episode psychosis patients during the first year of the antipsychotic treatment and 19 controls. While corroborating several earlier findings when comparing cases and controls and the effects of the antipsychotic medication, we also found that prospective weight gain in psychotic patients was associated with increased levels of triacylglycerols with low carbon number and double-bond count at baseline, that is, lipids known to be associated with increased liver fat. Our study suggests that metabolite profiles may be used to identify the psychotic patients most vulnerable to develop metabolic co-morbidities, and may point to a pharmacological approach to counteract the antipsychotic-induced weight gain.

White matter hyperintensities and cognitive performance in adult patients with bipolar I, bipolar II, and major depressive disorders.

PURPOSE: We evaluate for the first time the associations of brain white matter hyperintensities (WMHs) on magnetic resonance imaging (MRI) with neuropsychological variables among middle-aged bipolar I (BPI), II (BPII) and major depressive disorder (MDD) patients and controls using a path model. METHODS: Thirteen BPI, 15 BPII, 16 MDD patients, and 21 controls underwent brain MRI and a neuropsychological examination. Two experienced neuroradiologists evaluated WMHs on the MRI scans. We constructed structural equation models to test the strength of the associations between deep WMH (DWMH) grade, neuropsychological performance and diagnostic group. RESULTS: Belonging in the BPI group as opposed to the control group predicted higher DWMH grade (coefficient estimate 1.13, P=0.012). The DWMH grade independently predicted worse performance on the Visual Span Forward test (coefficient estimate -0.48, P=0.002). Group effects of BPI and MDD were significant in predicting poorer performance on the Digit Symbol test (coefficient estimate -5.57, P=0.016 and coefficient estimate -5.66, P=0.034, respectively). LIMITATIONS: Because of the small number of study subjects in groups, the negative results must be considered with caution. CONCLUSIONS: Only BPI patients had an increased risk for DWMHs. DWMHs were independently associated with deficits in visual attention.

Accuracy of register- and record-based bipolar I disorder diagnoses in Finland; a study of twins.

Registers have been widely used in schizophrenia studies. For bipolar disorder, the use has been more limited and no studies exist concerning accuracy of bipolar I diagnoses in registers. We have collected an unselected twin sample for a study of bipolar I disorder. We report here the diagnostic procedures and accuracy of bipolar I diagnoses in a nation-wide hospital discharge registry. We evaluated also the accuracy of the medical record-based best-estimate diagnoses, comparing these with the SCID interview diagnoses. From the National Hospital Discharge Register we identified all like-sex twins, born 1940-1957, (N=42), and all like- or opposite-sex twins, born 1961-1969, (N=15), who had at least once a diagnosis of bipolar I disorder. The best-estimate diagnoses based on medical records, and were made by two doctors blind to each other, and according to DSM-IV-criteria. Diag-noses were then confirmed by SCID interviews, with the mi-nimum follow-up time after the first admission being 6 years. The accuracy of bipolar diagnoses in the register was 92% and 87%, accordingly. When comparing the best-estimate diagnoses to SCID interview diagnoses, there was one false positive case in the first sample, 3.4% [95% CI 0.1% to 7.8%], and none in the second sample. Our study shows that a diagnosis of bipolar I disorder in the hospital discharge register, or if based only on medical records, is highly reliable and stable. These results strengthen the usefulness of regis-ters also in bipolar disorder.

Bipolar disorder susceptibility region on Xq24-q27.1 in Finnish families.

Bipolar disorder (BPD) is a common disorder characterized by episodes of mania, hypomania and depression. The genetic background of BPD remains undefined, although several putative loci predisposing to BPD have been identified. We have earlier reported significant evidence of linkage for BPD to chromosome Xq24-q27.1 in an extended pedigree from the late settlement region of the genetically isolated population of Finland. Further, we established a distinct chromosomal haplotype covering a 19 cM region on Xq24-q27.1 co-segregating with the disorder. Here, we have further analyzed this X-chromosomal region using a denser marker map and monitored X-chromosomal haplotypes in a study sample of 41 Finnish bipolar families. Only a fraction of the families provided any evidence of linkage to this region, suggesting that a relatively rare gene predisposing to BPD is enriched in this linked pedigree. The genome-wide scan for BPD predisposing loci in this large pedigree indicated that this particular X-chromosomal region provides the best evidence of linkage genome-wide, suggesting an X-chromosomal gene with a major role for the genetic predisposition of BPD in this family.