Reframing Psychiatry for Precision Medicine

Elizabeth B. Torres

doi:10.3390/jpm10040144

Abstract

The art of observing and describing behaviors has driven diagnosis and informed basic science in psychiatry. In recent times, studies of mental illness are focused on understanding the brain’s neurobiology but there is a paucity of information on the potential contributions from peripheral activity to mental health. In precision medicine, this common practice leaves a gap between bodily behaviors and genomics that we here propose to address with a new layer of inquiry that includes gene expression on tissues inclusive of brain, heart, muscle-skeletal and organs for vital bodily functions. We interrogate gene expression on human tissue as a function of disease-associated genes. By removing genes linked to disease from the typical human set, and recomputing gene expression on the tissues, we can compare the outcomes across mental illnesses, well-known neurological conditions, and non-neurological conditions. We find that major neuropsychiatric conditions that are behaviorally defined today (e.g., autism, schizophrenia, and depression) through DSM-observation criteria have strong convergence with well-known neurological conditions (e.g., ataxias and Parkinson’s disease), but less overlap with non-neurological conditions. Surprisingly, tissues majorly involved in the central control, coordination, adaptation and learning of movements, emotion and memory are maximally affected in psychiatric diagnoses along with peripheral heart and muscle-skeletal tissues. Our results underscore the importance of considering both the brain–body connection and the contributions of the peripheral nervous systems to mental health.

Highlights

Modern medicine is at an inflexion point [1], whereby advances in computational methods, wearable sensing technology and open access to Big Data are reshaping the ways in which we inform basic science and rapidly translate our knowledge to actionable treatments
Combining information about gene expression on tissues that involve key components of the central nervous systems, key organs for vital bodily functions, muscle-skeletal tissues and nerves, and cardiac tissues, we explore the effects of removing disease-associated genes, on the overall remaining genome expression on these tissues
Tissue gene expression was modelled by the exponential distribution y = λe−λx, with x as the gene combination expressed in the tissues, and λ as the exponential rate parameter

Summary

Introduction

Modern medicine is at an inflexion point [1], whereby advances in computational methods, wearable sensing technology and open access to Big Data are reshaping the ways in which we inform basic science and rapidly translate our knowledge to actionable treatments. Psychiatry is one of those medical fields that is rapidly evolving, while adapting traditional models to help advance the main goal of helping patients improve their quality of life. Along those lines, computational psychiatry [2], a nascent subfield within psychiatry, is merging methods from Computational Neuroscience with clinical approaches through successful collaborations. Computational psychiatry [2], a nascent subfield within psychiatry, is merging methods from Computational Neuroscience with clinical approaches through successful collaborations These new developments are bound to open new frontiers in therapeutic treatments. As part of a more general effort in the medical field, precision medicine (PM) [1] has emerged as a new platform to combine expertise from multiple layers of the knowledge network in order to design personalized targeted treatments (Figure 1A).

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Conclusion