Restoring the missing person to personalized medicine and precision psychiatry

Abstract

Precision psychiatry has emerged as part of the shift to personalized medicine and builds on frameworks such as the U.S. National Institute of Mental Health Research Domain Criteria (RDoC), multilevel biological “omics” data and, most recently, computational psychiatry. The shift is prompted by the realization that a one-size-fits all approach is inadequate to guide clinical care because people differ in ways that are not captured by broad diagnostic categories. One of the first steps in developing this personalized approach to treatment was the use of genetic markers to guide pharmacotherapeutics based on predictions of pharmacological response or non-response, and the potential risk of adverse drug reactions. Advances in technology have made a greater degree of specificity or precision potentially more attainable. To date, however, the search for precision has largely focused on biological parameters. Psychiatric disorders involve multi-level dynamics that require measures of phenomenological, psychological, behavioral, social structural, and cultural dimensions. This points to the need to develop more fine-grained analyses of experience, self-construal, illness narratives, interpersonal interactional dynamics, and social contexts and determinants of health. In this paper, we review the limitations of precision psychiatry arguing that it cannot reach its goal if it does not include core elements of the processes that give rise to psychopathological states, which include the agency and experience of the person. Drawing from contemporary systems biology, social epidemiology, developmental psychology, and cognitive science, we propose a cultural-ecosocial approach to integrating precision psychiatry with person-centered care.

A cultural-ecosocial systems view for psychiatry

“…Crucially, these models can include clinician-patient interaction and other social processes as part of the symptom network. Innovative computational methods can capture multilevel system dynamics if the relevant data are collected ( 264 ). The resultant models could be used as decision tools or used by clinicians and patients to foster mutual understanding and motivate interventions.…”

“…These domains can provide a temporal dimension to clinical formulation that points both to adaptive challenges and resources for helping, healing and recovery. Efforts to develop models that incorporate social context and lived experience are underway, but they face multiple obstacles, including lack of collection of data representative of population variability and high levels of context dependence as well as ethical and pragmatic issues related to the use of such data ( 264 ). We need better conceptual, research and clinical tools to characterize niches—their demands, affordances, and constraints as well as their embedding in larger ecosystems ( 6 ).…”

Harmonizing Big Data in Mental Health Research: A Proof-of-Principle in the R2D2-MH Consortium Using the International Classification of Functioning (ICF)

“…Rather than seeking to provide support based on diagnostic categories, treatment and support options that can be delivered based upon an individual's unique needs and strength pro les 17 . Precision approaches in psychiatry have largely been focused on biomarkers and pharmacological interventions, however, this focus has attracted some criticism, in part, due to its neglect of socialenvironmental factors that may in uence etiology and outcomes, and the need to consider developmental trajectories 15 . Indeed, environmental in uences are widely documented and cannot be ignored in psychiatric investigation 37,41,55,56 .…”

“…Some more biologically oriented consortia such as the ENIGMA Consortium; 14 have developed some solutions to generating big data, but these approaches remain concentrated on biological mechanisms, with less focus on other bio-psycho-social information. Harmonizing more diverse bio-psycho-social data in psychiatry introduces additional heterogeneity and di culties, yet, aggregating such data is necessary to psychiatry where there is considerable between and within-person variation in biological, cognitive, psychological, and socio-environmental characteristics that must be captured 15 . Even when challenges to harmonization are overcome, current methods may result in big data not optimally suited to advancing psychiatric research, often remaining embedded in paradigms that more contemporary approaches have superseded.…”

Editorial: Non-canonical pathways of psychiatric drugs: beyond their neurotransmitter action

“…Specifically, immuneresponse modulators, histone deacetylase (HDAC) inhibitors, and the purinergic P2X7 receptor (P2X7R) arise as promising pharmacological targets for BD treatment, mainly owing to their anti-inflammatory properties, but also their neuroplasticity properties. The insights and debates addressed in this manuscript advance the quest for precision psychiatry (Gómez-Carrillo et al, 2023), which requires that both diagnosis and therapy go beyond the traditional neurotransmitter hypothesis for BD.…”