S44. NEUROBIOLOGICAL FINGERPRINTS OF COGNITIVE SUBTYPES IN RECENT ONSET PSYCHOSIS PATIENTS
Authors: Wenzel Julian , Dwyer Dominic B , Ruef Anne , Öztürk Ömer , Haas Shalaila , Kambeitz Joseph , Brambilla Paolo , Koutsouleris Nikolaos , Kambeitz-Ilankovic Lana 
Published: May 2020

Background

Neurocognitive impairment plays a central role in pathogenesis and course of psychotic disorders. Patients suffering from psychosis or psychosis-related diseases show general and specific neurocognitive impairments that often precede the onset of manifest symptoms. Neurocognitive impairments are frequently associated with reduced psychosocial functioning along with altered brain morphology and function. Quantifying neurocognitive heterogeneity in impairment in schizophrenia patients, cluster analytic approaches differentiated several cognitive subtypes, including a generally impaired and generally spared subgroup. An independent set of findings provided evidence that neurocognitive subgroups of cognitively spared and impaired SZ patients can also be differentiated based on their brain morphology. The current study aims to (1) subtype a first episode psychosis sample based on neurocognitive performance using cluster analysis and (2) investigate grey matter (GM) differences between the obtained cognitive subtypes and healthy volunteers.

Methods

121 recent onset-psychosis (ROP) patients and 201 healthy controls (HC) were recruited within the framework of the Personalized Prognostic Tool for Early Psychosis Management (PRONIA) project. Patients fulfilled DSM-IV-TR criteria of a first affective or non-affective psychotic episode in the last 3 month with onset in the last 24 months. Cognitive subtypes of the ROP patients were derived from 83 variables of 10 neurocognitive tasks using a kmeans clustering algorithm. A resampling approach implemented in R was used to assess the statistical stability of the results. Neuropsychological and clinical cluster characteristics were assessed using t tests. GM volume of the obtained patient clusters was compared by means of intracranial volume corrected t tests with age, sex and site matched HCs using SPM.

Results

The analysis reveals a stable two-cluster solution: A higher cognitive performance cluster (HCP; N=71) and a lower cognitive performance cluster (LCP; N=39). Patients assigned to HCP performed significantly (p &lt; 0.01) worse in 4 out of 10 neuropsychological tasks. Patients assigned to LCP performed significantly (p &lt; 0.01) worse in 9 out of 10 neuropsychological tasks. LCP patients show significantly lower premorbid IQ (p &lt; 0.001) and General Assessment of Functioning score (GAF; p &lt; 0.01), lower occupational functioning (p &lt; 0.01) and higher values on the negative component of the Positive and Negative Syndrom Scale (PANSS; p &lt; 0.05). They show no demographical differences regarding age, sex, education years and study site. LCP patients reveal widespread GM reductions in bilateral temporal, parietal and frontal brain regions as compared to healthy controls. GM reductions of the HCP cluster are more restricted and evident in temporal, occipital regions and in the anterior cingulum.

Discussion

Two homogeneous, neurocognitive subgroups of patients suffering from a recent psychotic episode were identified and show distinctive psychopathological and neuroanatomical patterns. The obtained GM reductions in LCP go in line with the neuro-developmental origin of the disease affecting premorbid cognitive and occupational functioning as well as the STG which was reported to be decreased in the early course of the disease. Finding subgroups within early stage psychotic patients with minimal intake of antipsychotic medication, suggests different underlying patho(-physio)logical mechanisms predating manifest illness expression. This evidence offers the opportunity for personalizing interventions like neurocognitive trainings to enhance patients’ odds for recovery after psychosis.