Plasma Phosphorylated Tau 231 Increases at One-Year Intervals in Cognitively Unimpaired Subjects.

Background: Plasma biomarkers of Alzheimer's disease (AD) constitute a non-invasive tool for diagnosing and classifying subjects. They change even in preclinical stages, but it is necessary to understand their properties so they can be helpful in a clinical context. Objective: With this work we want to study the evolution of p-tau231 plasma levels in the preclinical stages of AD and its relationship with both cognitive and imaging parameters. Methods: We evaluated plasma phosphorylated (p)-tau231 levels in 146 cognitively unimpaired subjects in sequential visits. We performed a Linear Mixed-effects Model to analyze their rate of change. We also correlated their baseline levels with cognitive tests and structural and functional image values. ATN status was defined based on cerebrospinal fluid biomarkers. Results: Plasma p-tau231 showed a significant rate of change over time. It correlated negatively with memory tests only in amyloid-positive subjects. No significant correlations were found with any imaging measures. Conclusions: Increases in plasma p-tau231 can be detected at one-year intervals in cognitively healthy subjects. It could constitute a sensitive marker for detecting early signs of neuronal network impairment by amyloid.

Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients.

Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either "continuous" (n=94) or "remitting" (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improved in some samples. This study provides proof of concept that combining multi-center MRI data to create a well performing classification model is possible. However, to create complex multi-center models that perform accurately, each center should contribute a sample either large or homogeneous enough to first allow accurate classification within the single-center.

Caudate nucleus volume and its clinical and cognitive correlations in first episode schizophrenia.

OBJECTIVE: Striatal dysfunction has been traditionally implicated in the pathophysiology of schizophrenia. The purpose of this study is to examine the relationship between caudate nucleus volumes and clinical and cognitive features of schizophrenic patients in an early phase of their illness. METHODS: Caudate nucleus volumes in previously untreated first episode patients with non-affective psychosis (N=76) and healthy comparison subjects (N=45) were measured. Caudate nucleus volume in the right and left hemispheres were automatically segmented and analyzed using BRAINS2. Analysis of covariance was used to control for intracranial volume. Severity of clinical symptoms was assessed using SAPS and SANS total scores. The relationship between cognitive dimensions, and caudate nucleus volume was evaluated. Finally, we examined the correlation between caudate volumes and the duration of untreated illness (DUI), duration of untreated psychosis (DUP) and duration of prodrome period (DPP). RESULTS: Right, left, and total caudate nucleus volumes did not differ significantly between patients and controls. Those patients with a longer DUP have smaller caudate nucleus. In addition, caudate nucleus volume was positively correlated with the severity of psychotic symptomatology. No significant associations were found between caudate nucleus volume and cognitive functioning. CONCLUSION: This group of first episode schizophrenia patients did not exhibit significant volumetric anomalies of the caudate nucleus. Despite this lack of volumetric abnormalities, a delay in receiving antipsychotic treatment and the severity of initial positive symptomatology were significantly associated with reduced caudate volume.