Biologically Annotated Heterogeneity of Depression through Neuroimaging Normative Modeling.

Depression is not a unitary disorder but is rather heterogeneous in nature. Likewise, no two depressive individuals are entirely alike, and therefore, their associated symptoms are also highly personalized. Over the past decade, numerous approaches have been developed to identify neuroimaging-derived biomarkers for advancing our understanding of the neurobiology of depressive patients at the group level. However, substantial clinical heterogeneity among individuals with depression hinders the development of biomarkers for personalized interventions. Recently, publicly available resources have enabled researchers to investigate precision neuromarkers for depression using integrative multi-neuroimaging approaches. In this review, we systematically revisit previous findings and discuss the advances in data-driven neuroimaging analyses for depression heterogeneity, including the disentangling of dimensional and overlapping strategies, individual-specific abnormal patterns based on normative modeling frameworks, and associations between multiscale organizations. We also discuss the limitations, challenges, and future directions for depression heterogeneity. A summary of these advances is crucial for enhancing the understanding of the neurobiology of depression and will facilitate more accurate diagnoses and personalized interventions.