A statistical methodology to improve accuracy in differentiating schizophrenia patients from healthy controls

Factorial structure of the Comprehensive Assessment of At-Risk Mental States in help-seeking individuals: mapping the structure and the prediction of subsequent transition to psychosis

Objectives

The aim of the current study was 3-fold: 1) to examine the factorial structure of the Comprehensive Assessment of At-Risk Mental States (CAARMS) in help-seeking individuals undergoing an assessment on suspicion of psychosis risk; 2) to investigate the association of CAARMS factors with functioning; 3) and to test the association of any derived factors with the longitudinal outcome of transition to psychosis.

Methods

The study included 101 patients. First, a principal component analysis (PCA) was conducted using the Varimax rotation method. A minimum initial eigenvalues of greater than or equal to 1.0, analysis of Scree plots, percentage of variance explained by each component, reliability (Cronbach's alpha) of factors above 0.7 and Parallel Analysis were the criteria used to determine the appropriate number of factors Second, Spearman correlations were run to analyze the relationship between CAARMS factors and sociodemographic and functional variables (i.e. age, schooling, Social and Occupational Functioning Assessment Scale-SOFAS- and Health of the Nation Outcome Scales-HoNOS- scores). Third, we performed a Logistic regression analysis to evaluate the association between baseline CAARMS factors and the risk of transition to psychosis at the 6-month follow-up.

Results

A total of 101 consecutive patiens were recruited. We found that: 1) a 6 factor model solution as the most appropriate, jointly accounting for 65% of the variance; 2) factors 1 ("negative-interpersonal"), 2 ("cognitive-disorganization"), 3 ("positive"), and 4 ("motor-physical changes") were negatively correlated with SOFAS total score; factors 1, 2, and 3 showed positive correlations with HoNOS total score; factors 2 and 3 present similar patterns of correlations, factor 3 manifesting the strongest association with HoNOS symptoms, HONOS and SOFAS total score. Both factors 5 and 6 show significant associations with HoNOS behavioral impairment; 3) after 6 months 28 participants (30.1%) converted to psychosis. Factors 2 and 3 were positively associated with the risk of transition to psychosis; whereas, the factor 5 ("affective factor") was negatively associated with the outcome variable.

Conclusions

It is thus crucial to recognize the type and severity of psychopathology in help-seeking individuals in order to intensive clinical monitoring of subclinical psychopathology risk profiles, and design specific care pathways.

Prioritizing schizophrenia endophenotypes for future genetic studies: An example using data from the COGS-1 family study

Past studies describe numerous endophenotypes associated with schizophrenia (SZ), but many endophenotypes may overlap in information they provide, and few studies have investigated the utility of a multivariate index to improve discrimination between SZ and healthy community comparison subjects (CCS). We investigated 16 endophenotypes from the first phase of the Consortium on the Genetics of Schizophrenia, a large, multi-site family study, to determine whether a subset could distinguish SZ probands and CCS just as well as using all 16. Participants included 345 SZ probands and 517 CCS with a valid measure for at least one endophenotype. We used both logistic regression and random forest models to choose a subset of endophenotypes, adjusting for age, gender, smoking status, site, parent education, and the reading subtest of the Wide Range Achievement Test. As a sensitivity analysis, we re-fit models using multiple imputations to determine the effect of missing values. We identified four important endophenotypes: antisaccade, Continuous Performance Test-Identical Pairs 3-digit version, California Verbal Learning Test, and emotion identification. The logistic regression model that used just these four endophenotypes produced essentially the same results as the model that used all 16 (84% vs. 85% accuracy). While a subset of endophenotypes cannot replace clinical diagnosis nor encompass the complexity of the disease, it can aid in the design of future endophenotypic and genetic studies by reducing study cost and subject burden, simplifying sample enrichment, and improving the statistical power of locating those genetic regions associated with schizophrenia that may be the easiest to identify initially.

Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia part I: Neurophysiology

The neurophysiological components that have been proposed as biomarkers or as endophenotypes for schizophrenia can be measured through electroencephalography (EEG) and magnetoencephalography (MEG), transcranial magnetic stimulation (TMS), polysomnography (PSG), registration of event-related potentials (ERPs), assessment of smooth pursuit eye movements (SPEM) and antisaccade paradigms. Most of them demonstrate deficits in schizophrenia, show at least moderate stability over time and do not depend on clinical status, which means that they fulfil the criteria as valid endophenotypes for genetic studies. Deficits in cortical inhibition and plasticity measured using non-invasive brain stimulation techniques seem promising markers of outcome and prognosis. However the utility of these markers as biomarkers for predicting conversion to psychosis, response to treatments, or for tracking disease progression needs to be further studied.

1H-MRS glutamate level predicts auditory sensory gating in alcohol dependence: Preliminary results

Background:

Impairment in auditory sensory gating (ASG) has been documented in alcohol dependence [1]. Likewise, it has been shown that ASG becomes abnormal during alcohol administration in otherwise healthy individuals [2]. Patterns of gating abnormality associated with alcohol use are likely associated with an alcohol responsive neurochemical like glutamate (Glu), particularly since it is well-established that alcohol affects NMDA receptors and that glutamatergic functioning is abnormal in both acute alcohol use and in alcohol dependence [3]. Hence, a link between Glu metabolite levels and ASG was hypothesized. It was first hypothesized that Glu and ASG abnormality would be found in groups with alcohol dependence. A second hypothesis was that across groups, greater Glu would predict reduced ASG.

Methods:

Groups were comprised of healthy, non-drinking controls (Controls, N = 4), individuals with current alcohol dependence (AUD-current, N = 6), and with alcohol dependence in remission for at least 1 year (AUD-remission, N = 6). Participants underwent a diagnostic assessment for alcohol consumption, MRI, 1H-MRS for in vivo assessment of Glu and other metabolites, and MEG scanning during a paired click protocol. ASG was computed as the ratio of the source strength of the 50 ms component in the event related field (ERF) to the second click in the pair divided by the source strength of the 50 ms component to the first click in the pair.

Results:

Univariate MANOVAs controlling for age and gender revealed a significant effect for group on Glu and ASG, such that ASG ratios were significantly elevated, implying weakened gating. Glu concentration was reduced in AUD-current relative to the other two groups. Further analysis revealed that when additionally controlling for the group effect, reduced Glu predicted increasing impairment in ASG.

Conclusions:

The overall results were consistent with the hypothesis that differences in Glu metabolite levels associated with alcohol dependence result in impaired ASG.