Predicting Remission in Subjects at Clinical High Risk for Psychosis Using Mismatch Negativity

Kim, Minah; Lee, Tak Hyung; Yoon, Youngwoo Bryan; Lee, Tae Young; Kwon, Jun Soo

doi:10.1093/schbul/sbx102

Cited by 35 publications

(42 citation statements)

References 43 publications

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“…This study revealed that the MMN could be a significant predictor for remission and symptom improvement, as well as functional outcomes, in patients with schizophrenia. Recent studies showed that MMN was a putative predictor of symptom improvement and remission, regardless of the transition to a psychotic disorder in subjects at high clinical risk [18]. This study proposed that MMN could be associated with remission, not only in subjects at high clinical risk but also in the patients diagnosed with schizophrenia.…”

Section: Discussionmentioning

confidence: 89%

“…These stimuli were presented through MDR-D777 headphones (Sony, Tokyo, Japan). The peak amplitude and latency of the MMN were determined as the most negative peak between 130 milliseconds and 250 milliseconds of the subtracted waveform using a peak detection method at six electrode sites (Fz, F3, F4, FCz, FC3, and FC4) [18].…”

Section: Data Acquisition and Analysismentioning

confidence: 99%

“…However, no previous studies have completely explored the relationships between early auditory processing MMN and remission in patients with schizophrenia. A recent study reported that MMN was a putative predictor of prognosis, regardless of the transition to psychotic disorders in subjects at high clinical risk [18]. It revealed that MMN could predict the remission of subjects at high clinical risk [18], but the population of the study had not yet been diagnosed with schizophrenia.…”

Section: Introductionmentioning

confidence: 95%

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Mismatch Negativity Indices as a Prognostic Factor for Remission in Schizophrenia

Kim

Kwon

Lee

et al. 2020

Clin Psychopharmacol Neurosci

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Objective: Mismatch negativity (MMN) is known to be associated with neuro-cognition and functional outcomes. Remission and recovery rates are related to the neuro-cognition of patients with schizophrenia. The present study explored the relationship of MMN with remission in patients with schizophrenia. Methods: Forty patients with schizophrenia were recruited and divided into two groups, with or without remission, according to the Remission in Schizophrenia Working Group criteria (RSWGcr). Symptom severity (Positive and Negative Syndrome Scale, PANSS), cognitive function, functional outcome, and MMN of the patients were evaluated. A regression analysis was used to identify the factors that significantly predicted symptom improvement and remission including MMN at frontal site assessed at baseline, and anticipated clinical variables as predictive factors. Results: MMN amplitudes in frontal sites were further decreased in the groups without remission compared to the groups with remission. MMN amplitude was significantly correlated with measures of symptom change and functional outcome measurements in patients with schizophrenia. Regression analysis revealed that symptom severity and MMN significantly predicted remission in patients with schizophrenia. Symptom improvement significantly predicted PANSS at baseline, illness duration, and antipsychotic dose, as did MMN amplitude at frontal site. Conclusion: Our results suggest that MMN reflected symptom improvement and remission in patients with schizophrenia. MMN indices appear to be promising candidates as predictive factors for schizophrenia remission.

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Section: Discussionmentioning

confidence: 89%

Section: Data Acquisition and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

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Mismatch Negativity Indices as a Prognostic Factor for Remission in Schizophrenia

Kim

Kwon

Lee

et al. 2020

Clin Psychopharmacol Neurosci

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“…It has been reported that a shorter duration of untreated psychosis is associated with a greater response to antipsychotic treatment in first-episode schizophrenia [ 58 ]. Our results indicated that patients with a higher level of education achieved greater clinical improvement, which was predictable from the improvement in attenuated positive symptoms among individuals at high risk [ 59 ]. However, why different clinical features affect different clinical categories might need to be explored in greater detail in the future.…”

Section: Discussionmentioning

confidence: 99%

Progressive Grey Matter Volume Changes in Patients with Schizophrenia over 6 Weeks of Antipsychotic Treatment and Their Relationship to Clinical Improvement

Zhang

Liao

et al. 2018

Neurosci. Bull.

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Cross-sectional and longitudinal studies have identified widespread and progressive grey matter volume (GMV) reductions in schizophrenia, especially in the frontal lobe. In this study, we found a progressive GMV decrease in the rostral medial frontal cortex (rMFC, including the anterior cingulate cortex) in the patient group during a 6-week follow-up of 40 patients with schizophrenia and 31 healthy controls well-matched for age, gender, and education. The higher baseline GMV in the rMFC predicted better improvement in the positive score on the Positive and Negative Syndrome Scale (PANSS), and this might be related to the improved reality-monitoring. Besides, a higher baseline GMV in the posterior rMFC predicted better remission of general symptoms, and a lesser GMV reduction in this region was correlated with better remission of negative symptoms, probably associated with ameliorated self-referential processing and social cognition. Besides, a shorter disease course and higher educational level contributed to better improvement in the general psychopathological PANSS score, and a family history was negatively associated with improvement of the negative and total PANSS scores. These phenomena might be important for understanding the neuropathological mechanisms underlying the symptoms of schizophrenia and for making clinical decisions.

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“…In a 6-year follow-up study comparing 47 healthy controls and 48 participants with CHR for psychosis, CHR nonremitters had reduced MMN at baseline compared to CHR remitters and healthy controls. The baseline MMN was the only significant predictor of remission [28]. …”

mentioning

confidence: 99%

Attenuated Mismatch Negativity in Attenuated Psychosis Syndrome Predicts Psychosis: Can Galantamine-Memantine Combination Prevent Psychosis?

Koola

2018

Complex Psychiatry

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Although first proposed in 1987, early diagnosis and intervention of psychotic disorders has only recently become a priority in the field. The interest in clinical high risk (CHR) for psychosis skyrocketed after attenuated psychosis syndrome (APS) was added to the DSM-5. There is evidence that in individuals with APS, attenuated mismatch negativity (MMN: functioning of the auditory sensory memory system) is a robust biomarker that can predict transition to psychosis. The underlying pathophysiological mechanism of MMN is via the interaction of N-methyl-D-aspartate (NMDA) and alpha-7 nicotinic acetylcholine (α-7nACh) receptors. Galantamine is an acetylcholinesterase inhibitor and a positive allosteric modulator of the α-7nACh receptors. Memantine is an NMDA receptor antagonist. Memantine has been shown to enhance MMN in people with schizophrenia. Although no studies with galantamine have measured MMN, encenicline, an α-7 nicotinic partial agonist, increased MMN in people with schizophrenia. MMN has been suggested as a potential biomarker with the galantamine-memantine combination for the treatment of neuropsychiatric disorders. Hence, the galantamine-memantine combination may enhance MMN, thereby preventing CHR to psychosis. With no treatments available, randomized controlled trials are warranted with the galantamine-memantine combination to delay or prevent conversion to psychosis in individuals with CHR.

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Predicting Remission in Subjects at Clinical High Risk for Psychosis Using Mismatch Negativity

Abstract: These results suggest that MMN is a putative predictor of prognosis regardless of the transition to psychotic disorder in subjects at CHR. Early prognosis prediction and the provision of appropriate interventions based on the initial CHR status might be aided using MMN.

Cited by 35 publications

References 43 publications

Mismatch Negativity Indices as a Prognostic Factor for Remission in Schizophrenia

Mismatch Negativity Indices as a Prognostic Factor for Remission in Schizophrenia

Progressive Grey Matter Volume Changes in Patients with Schizophrenia over 6 Weeks of Antipsychotic Treatment and Their Relationship to Clinical Improvement

Attenuated Mismatch Negativity in Attenuated Psychosis Syndrome Predicts Psychosis: Can Galantamine-Memantine Combination Prevent Psychosis?

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