Valoración funcional mediante estimulación magnética transcraneal de la transmisión inhibitoria en esquizofrenia

Resumen

After years of huge research efforts, there is still not a basic understanding of the pathophysiological mechanisms of schizophrenia. Different lines of evidence suggest that schizophrenia is likely a heterogeneous condition that encompasses different presentations and subtypes. The view of schizophrenia as a singular disease entity could have led to an inadequate study approach and thus, to the lack of replicability and inconsistency of the research findings in the field. The present doctoral thesis sought to address this heterogeneity considering two important facts. First, a change in the schizophrenia construct as a syndrome should be followed by a change in its research approach. Second, this change should also be accompanied by a change in the study focus, which has traditionally been far distant from the altered functions in this syndrome. Therefore, the general aims of this thesis were threefold: i) to explore de existence of patients subgroups within schizophrenia using a data-driven approach; ii) to follow-up the clinical and real-life outcomes of the identified subgroups in the medium term; and iii) to assess a neurobiological substrate closer to the psychological functions known to be altered in schizophrenia. This doctoral thesis includes four studies. The two first studies explored the existence of subgroups within the schizophrenia syndrome using a data-driven approach based on cognition and functional network properties of the electroencephalogram (EEG), respectively. The third study assessed the clinical and functional outcomes of the previously identified cognitive subgroups. Finally, the last study focused on exploring the association between the decreased task-related activity modulation observed in the first two subgroups studies and the inhibitory system function. All patients were diagnosed according to the Statistical Manual of Mental Disorders 5th edition (DSM-V) criteria and their symptoms were assessed through the Positive and Negative Syndrome Scale (PANSS). Results from the first study showed a severely impaired and a moderately impaired subgroup of patients based on cognitive impairments. Moreover, the severely impaired group was associated with higher symptom scores and larger neurobiological alterations. In the second study, we were able to identify two subgroups of patients within the schizophrenia syndrome using EEG-based network parameters derived from graph theory and obtained during an auditory oddball task. One subgroup showed altered global properties of functional and structural connectivity. The other subgroup showed an EEG network pattern similar to healthy controls. Remarkably, both subgroups studies showed that all identified patients subgroups were associated to task-related modulation deficits compared to healthy controls. The third study gave additional external validity to the described subgroups based on cognition. Results showed that the subgroup with larger cognitive impairments and more severe biological alterations was associated with greater clinical severity and more difficulties in real-life functioning in the medium term. Finally, the last study replicated the task-related cortical activity modulation deficit previously reported in schizophrenia patients. Moreover, results showed that patients with schizophrenia were associated with higher cortical reactivity following transcranial magnetic stimulation (TMS) single pulses over the dorsolateral prefrontal cortex compared to healthy controls. This finding is consistent with the decreased inhibitory function previously described in schizophrenia. Furthermore, we found a significant association between task-related activity modulation and the amplitude of the evoked response to TMS single pulses. In summary, the studies included in this doctoral thesis support the identification of different subgroups within the schizophrenia syndrome with different neurobiological underpinnings. Our findings highlight the fact that schizophrenia is likely not a single disorder entity but a collection of several distinct conditions with different substrates. In this line, data-driven methodologies seem to be a more suitable approach to encompass the large heterogeneity observed in schizophrenia.