Digital behavioural signatures reveal trans-diagnostic clusters of Schizophrenia and Alzheimer's disease patients

The current neuropsychiatric nosological categories underlie pragmatic treatment choice, reg-ulation and clinical research but does not encompass biological rationale. However, subgroups of patients suffering from schizophrenia or Alzheimer's disease have more in common than the neuropsychiatric nature of their condition, such as the expression of social dysfunction. The PRISM project presents here initial quantitative biological insights allowing the first steps toward a novel trans-diagnostic classification of psychiatric and neurological symptomatology intended to reinvigorate drug discovery in this area. In this study, we applied spectral clus-tering on digital behavioural endpoints derived from passive smartphone monitoring data in a subgroup of Schizophrenia and Alzheimer's disease patients, as well as age matched healthy controls, as part of the PRISM clinical study. This analysis provided an objective social function-ing characterization with three differential clusters that transcended initial diagnostic classi-fication and was shown to be linked to quantitative neurobiological parameters assessed. This emerging quantitative framework will both offer new ways to classify individuals in biologi-cally homogenous clusters irrespective of their initial diagnosis, and also offer insights into the pathophysiological mechanisms underlying these clusters.(c) 2023 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )