Reduced functional connectome uniqueness on the whole brain and network levels as a clinically relevant and reproducible neuroimaging marker in major depressive disorder.

BACKGROUND

Identifying reproducible neurobiological markers for Major Depressive Disorder (MDD) remains challenging due to methodological heterogeneity across neuroimaging studies. Functional connectome (FC) uniqueness, an individual-level metric derived from brain fingerprinting, quantifies the distinctiveness of intrinsic connectivity patterns and may offer a robust framework for biomarker discovery.

METHODS

We analyzed multi-site resting-state fMRI data from healthy controls (HC) and patients with Major Depressive Disorder (MDD), aged 19-37 years. Individual functional connectomes were constructed using 300 regions of interest grouped into 14 canonical networks. FC uniqueness was defined as the ratio of self-similarity (calculated as Pearson correlation between connectomes from the same individual across different time points) to similarity-to-others (calculated as Pearson correlations between an individual's connectome and those of other participants at the next timepoint). An FC uniqueness index greater than one indicates successful individual identification, referred to as fingerprinting accuracy.

RESULTS

Replicating prior studies, fingerprinting accuracy was highest at the whole-brain level, followed by the default mode and frontoparietal networks. MDD patients exhibited significantly lower FC uniqueness with pronounced reductions in frontoparietal and sensorimotor networks. Notably, reduced FC uniqueness was associated with higher PHQ-9 and BDI-II scores in this study.

LIMITATIONS: Comorbidity and age distribution differences may have introduced confounding effects.

CONCLUSIONS

Reduced FC uniqueness in frontoparietal and sensorimotor networks corelate with neurobiological organization in MDD and represents a reproducible, clinically interpretable neuroimaging marker with potential utility for diagnosis and stratification.