A subset of patients with schizophrenia experience physio-somatic symptoms reminiscent of chronic fatigue and fibromyalgia. In schizophrenia, these symptoms contribute to impaired quality of life, and are strongly related to neuro-cognitive deficits, and increased IgA responses to tryptophan catabolites. Negative and PHEM (psychosis, hostility, excitation, mannerism) symptoms, psychomotor retardation (PMR) and formal thought disorders, appear to be manifestations of a single trait reflecting overall severity of schizophrenia (OSOS). In this study, 120 patients with deficit schizophrenia (DEFSCZ) and 54 healthy subjects were assessed with the FibroFatigue (FF) rating scale, and the above-mentioned symptom domains as well as neuro-cognitive tests and biomarkers were measured. In DEFSCZ, there were robust associations between the FF score and all above-mentioned symptom domains, and impairments in semantic and episodic memory and executive functions. Furthermore, the FF score loaded highly on an OSOS latent vector (LV), which showed adequate convergent validity, internal consistency reliability and predictive relevance and fitted a reflective model. Soft Independent Modelling of Class Analogy (SIMCA) showed that the FF items discriminated DEFSCZ from controls with an overall accuracy of 100%. Interleukin IL-1β, IL-1 receptor antagonist (sIL-1RA), tumour necrosis factor (TNF)-α and CCL-11 (eotaxin) explained 66.8% of the variance in the FF score and 59.4% of the variance in OSOS. In conclusion, these data show that physio-somatic symptoms are a core component of the phenomenology of DEFSCZ and are largely mediated by neurotoxic effects of activated immune pathways, including aberrations in CCL-11, IL-1β and TNF-α signalling.

Amnestic mild cognitive impairment (aMCI) is a condition characterized by mild deficits in episodic and semantic memory and learning. The conversion rate of aMCI to Alzheimer disease (AD) is significantly higher in aMCI than in the general population. The aim of this study is to examine whether aMCI is a valid diagnostic category or whether aMCI comprises different subgroups based on cognitive functions. We recruited 60 aMCI patients, 60 with AD and 61 healthy controls who completed neuropsychological tests of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD-NP) and biomarkers including serum anion gap (AGAP). Principal component analysis, support vector machine and Soft Independent Modeling of Class Analogy (SIMCA) showed that AD patients and controls were highly significantly discrimanted from each other, while patients with aMCI overlap considerably with normal controls. SIMCA showed that 68.3% of the aMCI patients were assigned to the control class (named: aMCI-HC), 15% to AD (aMCI-AD), while 16.6% did not belong to either class (aMCI-strangers). aMCI-HC subjects showed sings of very mild cognitive decline and impaired recall. aMCI-strangers showed signs of mild cognitive impairment with impaired fluency and naming. aMCI-AD cases showed a cognitive profile reminiscent of AD an increased AGAP levels. In conclusion, our SIMCA model may classify subjects afforded a clinical diagnosis of aMCI according to Petersen’s criteria into three clinically relevant subgroups and help in the early detection of AD by identifying aMCI patients at risk to develop AD and those that have an AD prodrome.