Chaumette Boris, Yrondi Antoine, Godin Ophélia, Krebs Marie-Odile, Boyer Laurent, Samalin Ludovic, Llorca Pierre-Michel, Leboyer Marion
Université Paris Cité, Institut de psychiatrie et neurosciences de Paris (IPNP), Inserm U1266, Paris, France - Génétique humaine et fonctions cogniti ves, Institut Pasteur, CNRS UMR3571, Université Paris Cité, Paris, France - GHU-Paris Psychiatrie et Neurosciences, Hôpital Sainte-Anne, Paris, France - Department of Psychiatry, McGill University, Montréal, Canada.
Fondation Fondamental, Créteil, France - Service de psychiatrie et de psychologie médicale, Centre expert dépression résistante et trouble bipolaire, CHU de Toulouse, Hôpital Purpan, ToNIC centre de neuroimagerie, Université de Toulouse, Inserm, UPS, UMR1214, Toulouse, France.
Med Sci (Paris). 2025 May;41(5):416-424. doi: 10.1051/medsci/2025072. Epub 2025 May 26.
Precision psychiatry aims to identify homogeneous subgroups of patients using biomarkers, which could revolutionize current diagnostic frameworks and raise hopes for personalized treatments. Early examples in neuropsychiatry demonstrate the feasibility of this approach, such as the reclassification of dementias in neurology based on biomarkers such as amyloid plaques and tau proteins, and significant advances in neurodevelopmental disorders such as autism, where genetic heterogeneity has reshaped diagnostic perspectives. To achieve this vision, major challenges must be overcome, including the establishment of large transdiagnostic cohorts, the integration of multimodal data such as imaging, genomics, or digital phenotyping, and the application of advanced statistical methods such as clustering, normative modeling and digital twins. While this strategy promises more precise and effective care tailored to individual needs, it also challenges traditional classifications and forces the psychiatric community to rethink its foundational paradigms in light of biological knowledge.
精准精神病学旨在利用生物标志物识别患者的同质亚组,这可能会彻底改变当前的诊断框架,并为个性化治疗带来希望。神经精神病学的早期实例证明了这种方法的可行性,比如在神经病学中基于淀粉样斑块和tau蛋白等生物标志物对痴呆症进行重新分类,以及在自闭症等神经发育障碍方面取得的重大进展,其中遗传异质性重塑了诊断视角。为实现这一愿景,必须克服重大挑战,包括建立大型跨诊断队列、整合多模态数据(如图像、基因组学或数字表型)以及应用先进的统计方法(如聚类、规范建模和数字孪生)。虽然这一策略有望提供更精准、更有效的个性化护理,但它也对传统分类提出了挑战,并迫使精神病学界根据生物学知识重新思考其基础范式。