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Review
. 2020 Feb;25(2):243-253.
doi: 10.1038/s41380-019-0555-5. Epub 2019 Nov 1.

Identifying biological markers for improved precision medicine in psychiatry

Affiliations
Review

Identifying biological markers for improved precision medicine in psychiatry

Erin Burke Quinlan et al. Mol Psychiatry. 2020 Feb.

Abstract

Mental disorders represent an increasing personal and financial burden and yet treatment development has stagnated in recent decades. Current disease classifications do not reflect psychobiological mechanisms of psychopathology, nor the complex interplay of genetic and environmental factors, likely contributing to this stagnation. Ten years ago, the longitudinal IMAGEN study was designed to comprehensively incorporate neuroimaging, genetics, and environmental factors to investigate the neural basis of reinforcement-related behavior in normal adolescent development and psychopathology. In this article, we describe how insights into the psychobiological mechanisms of clinically relevant symptoms obtained by innovative integrative methodologies applied in IMAGEN have informed our current and future research aims. These aims include the identification of symptom groups that are based on shared psychobiological mechanisms and the development of markers that predict disease course and treatment response in clinical groups. These improvements in precision medicine will be achieved, in part, by employing novel methodological tools that refine the biological systems we target. We will also implement our approach in low- and medium-income countries to understand how distinct environmental, socioeconomic, and cultural conditions influence the development of psychopathology. Together, IMAGEN and related initiatives strive to reduce the burden of mental disorders by developing precision medicine approaches globally.

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Conflict of interest statement

Conflict of Interest

Dr. Banaschewski has served as an advisor or consultant to Actelion, Hexal Pharma,Bristol-Myers Squibb, Desitin Arzneimittel, Eli Lilly, Lundbeck, Medice, Neurim Pharmaceuticals, Novartis, Pfizer, and Shire, UCB, and Vifor Pharma; he has received conference attendance support, conference support, or speaking fees from Eli Lilly, Janssen McNeil, Medice, Novartis, and Shire, and UCB; and he is involved in clinical trials conducted by Eli Lilly, Novartis, and Shire and Viforpharma; he received royalities from Hogrefe, Kohlhammer, CIP Medien, Oxford University Press; the present work is unrelated to these relationships. Dr. Barker has received honoraria from General Electric Healthcare for teaching on scanner programming courses and acts as a consultant for IXICO. The other authors report no biomedical financial interests or potential conflicts of interest.

Figures

Figure 1
Figure 1
Classification accuracy of variables from six domains predicting age 16 binge drinking using data from age 14. Position on the x-axis represents the correlation between each variable and binge drinking. Based on data from Whelan et al 2014 . CANTAB = Cambridge Neuropsychological Test Automated Battery; ESPAD = European School Survey Project on Alcohol and Other Drugs; GMV = gray matter volume; LEQ = Life Events Questionnaire; MID = fMRI Monetary Incentive Delay task; NEO = NEO Personality Inventory; PBQ = Pregnancy and Birth Questionnaire; RT = reaction time; SURPS = Substance Use Risk Profile Scale; SST = fMRI Stop Signal Task; SWM = Spatial Working Memory; TCI = Temperament and Character Inventory.

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