Using biomarkers to inform diagnosis, guide treatments and track response to interventions in psychotic illnesses.

Commentary Using biomarkers to inform diagnosis, guide ­treatments and track ­response to interventions in psychotic illnesses “ As the clarification and development of neurophysiological biomarkers continues, shifts in our approach to diagnosis and treatment decisions should follow. After all, the success of precision medicine lies within these neuroscientific advances, and will likely be the roadmap to a next-generation brain-based Diagnostic and Statistical Manual. ” Keywords: mismatch negativity n neuroplasticity n psychosis n risk Following the release of the recently updated fifth edition of the Diagnostic and Statistical Manual (DSM‑V), psychiatry has fallen under fire from critics outside and even within the field [101,102] . Among the most frequently mentioned criti‑ cisms is that diagnosis and treatment decisions are based largely on patient reports, behavioral observation and our ability to make inferences about patients’ true inner experiences (e.g., clini‑ cal judgment), rather than objective laboratory tests. Psychiatric researchers have long recog‑ nized that our current symptom-based diag‑ nostic approach is inconsistent with our emerg‑ ing understanding of the overlapping ­neural networks that subserve multiple psychiatric ill‑ nesses [1] . To address these and other shortcom‑ ings, the National Institutes of Mental Health (NIMH) has launched the Research Domain Criteria Project (RDoC) as a framework for the next generation of neuropsychiatric research. In this forthcoming RDoC era, researchers are encouraged to directly assay deficiencies in neu‑ ral systems in order to guide diagnosis, develop and inform treatments, and predict and track outcomes. The RDoC aims to further expand our knowledge of brain–behavior relationships, and ultimately infuse this understanding of neu‑ ral dysfunction into clinical practice and accel‑ erate the development of more effective treat‑ ments. This paradigmatic shift toward “preci‑ sion medicine” joins brain-based disruption with clinical observation, serving to align patient and provider treatment goals for more effective out‑ comes. Here, we provide an example of a trans‑ latable EEG biomarker, mismatch negativity (MMN), that offers great promise for improv‑ ing our understanding, treatment, and perhaps even the prevention of a severely disabling and frequently intractable condition: psychosis. Many candidate biomarkers have provided critical insights into the pathophysiology of schizophrenia and related psychotic disorders. Some of these biomarkers include: prepulse inhibition of the acoustic startle reflex [2,3] , and EEG-based measures such as the P300 event- related potential amplitude [4] and cortical oscil‑ latory dynamics [5] . In this paper, we focus on MMN [6] . In concert with efforts to further infuse neuroscience into psychiatric assessment and care, an expert consensus panel formed as part of the Cognitive Neuroscience Treatment Research to Improve Cognition in Schizophre‑ nia (CNTRICS) initiative highlighted MMN as one of the more “mature” biomarkers that is “promising” and ready for immediate incorpo‑ ration into multisite clinical trials [7] . Recently, this measure has been described as a “break‑ through biomarker” [8] that is “translatable” [9] and potentially “the one we’ve been waiting for” [10] in neuropsychiatry. 10.2217/BMM.13. 133 Biomarkers Med. (2014) 8(1), 9–14 Auditory MMN: critical findings in psychosis Auditory MMN reflects an automatic change detection process that is elicited in response to unattended and infrequent sound stimuli embedded in a sequence of frequently presented standard stimuli. The MMN is elicited when a stimulus physically differs (e.g., in duration, pitch, intensity) from the context of the stan‑ dard trials, and also during a sequential pattern violation [11] . Importantly, because MMN does not require sustained task engagement or even consciousness [12,13] , it is thought to reflect an initial step from bottom-up sensory information processing leading to the conscious awareness of environmental change. MMN amplitude reduction in schizophrenia was first reported Veronica B Perez VISN-22 Mental Illness Research, Education & Clinical Center (MIRECC), VA San Diego Healthcare System, CA 92161, USA and Department of Psychiatry, University of California San Diego, La Jolla, CA, USA Neal R Swerdlow Department of Psychiatry, University of California San Diego, La Jolla, CA, USA David L Braff Department of Psychiatry, University of California San Diego, La Jolla, CA, USA Risto Naatanen Center of Functionally Integrative Neuroscience (CFIN), University of Arhus, Arhus, Denmark and Department of Psychology, University of Tartu, Tartu, Estonia and Institute of Behavioral Sciences, University of Helsinki, Helsinki, Finland Gregory A Light Author for correspondence: VISN-22 Mental Illness Research, Education & Clinical Center (MIRECC), VA San Diego Healthcare System, CA 92161, USA and Department of Psychiatry, University of California San Diego, La Jolla, CA, USA glight@ucsd.edu part of ISSN 1752-0363