Major depressive disorder (MDD) is a severe brain disease associated with a significant risk of suicide. Identification of suicidality is sometimes life-saving for MDD patients. We aimed to explore the use of dynamic functional network connectivity (dFNC) for suicidality detection in MDD patients. A total of 173 MDD patients, including 48 without suicide risk (NS), 74 with suicide ideation (SI), and 51 having attempted suicide (SA), participated in the present study. Thirty-eight healthy controls were also recruited for comparison. A sliding window approach was used to derive the dFNC, and the K-means clustering method was used to cluster the windowed dFNC. A linear support vector machine was used for classification, and leave-one-out cross-validation was performed for validation. Other machine learning methods were also used for comparison. MDD patients had widespread hypoconnectivity in both the strongly connected states (states 2 and 5) and the weakly connected state (state 4), while the dysfunctional connectivity within the weakly connected state (state 4) was mainly driven by suicidal attempts. Furthermore, dFNC matrices, especially the weakly connected state, could be used to distinguish MDD from healthy controls (area under curve [AUC] = 82), and even to identify suicidality in MDD patients (AUC = 78 for NS vs. SI, AUC = 88 for NS vs. SA, and AUC = 74 for SA vs. SI), with vision-related and default-related inter-network connectivity serving as important features. Thus, the dFNC abnormalities observed in this study might further improve our understanding of the neural substrates of suicidality in MDD patients.

BackgroundThe promoter variant rs17111237 in the CEP128 closely relates to radiotherapy (RT)‐related brain necrosis in nasopharyngeal carcinoma (NPC) patients.PurposeTo explore RT‐related dynamic alterations in brain morphology and their potential genetic mechanism, and to explore the modulatory effects of CEP128 genetic variants on RT‐related brain morphological alterations in NPC patients.Study TypeProspective, longitudinal.PopulationOne hundred one patients with histopathologic ally‐proven NPC (age 41.64 ± 9.63, 46 male), analyzed at baseline (pre‐RT), 3‐months post‐RT and 6 months post‐RT, and 19 sex‐, age‐ and education‐matched healthy controls.Field Strength/Sequence3D gradient echo brain volume (3D‐BRAVO) and diffusion‐weighted single‐shot spin‐echo echo‐planar sequences at 3.0 T.Assessmentrs17111237 in CEP128 was detected by Sanger sequencing. Structural and diffusion images were processed with FreeSurfer and FSL. Morphometric similarity network (MSN) was constructed with nine cortical indices derived from structural and diffusion images.Statistical TestsOne‐way ANOVA, chi‐square test. Pearson's correlation analysis was conducted to measure the relationship between CEP128 gene‐expression level in human brain and MSN alterations. Repeated analysis of variance performed to assess group differences in MSN and the modulatory effects of the CEP128 gene within patients. Significance level: P < 0.05, false‐discovery rate correction.ResultsRT‐related significant widespread MSN alterations were observed in the cortices of NPC patients. Notably, regional MSN alterations had a weak but significant negative correlation with the cortical pattern of CEP128 gene expression (r = −0.152). Furthermore, rs17111237 in the CEP128 had significant modulatory effects on the observed MSN alterations in NPC patients, with the modulatory effects being most obvious at 3 months post‐RT.ConclusionsMSN has potential to serve as a sensitive biomarker to detect RT‐related brain injury. Inter‐brain regional and inter‐patient variability of RT‐related brain injuries may be attributed to the cortical expression of the CEP128 gene and the modulatory effects of the promoter variant rs17111237 in CEP128.Evidence Level2Technical EfficacyStage 2

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