Dataset Information

Using resting-state intrinsic network connectivity to identify suicide risk in mood disorders.

ABSTRACT:

Background

Little is known about the neural substrates of suicide risk in mood disorders. Improving the identification of biomarkers of suicide risk, as indicated by a history of suicide-related behavior (SB), could lead to more targeted treatments to reduce risk.

Methods

Participants were 18 young adults with a mood disorder with a history of SB (as indicated by endorsing a past suicide attempt), 60 with a mood disorder with a history of suicidal ideation (SI) but not SB, 52 with a mood disorder with no history of SI or SB (MD), and 82 healthy comparison participants (HC). Resting-state functional connectivity within and between intrinsic neural networks, including cognitive control network (CCN), salience and emotion network (SEN), and default mode network (DMN), was compared between groups.

Results

Several fronto-parietal regions (k > 57, p < 0.005) were identified in which individuals with SB demonstrated distinct patterns of connectivity within (in the CCN) and across networks (CCN-SEN and CCN-DMN). Connectivity with some of these same regions also distinguished the SB group when participants were re-scanned after 1-4 months. Extracted data defined SB group membership with good accuracy, sensitivity, and specificity (79-88%).

Conclusions

These results suggest that individuals with a history of SB in the context of mood disorders may show reliably distinct patterns of intrinsic network connectivity, even when compared to those with mood disorders without SB. Resting-state fMRI is a promising tool for identifying subtypes of patients with mood disorders who may be at risk for suicidal behavior.

SUBMITTER: Stange JP

PROVIDER: S-EPMC7368462 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundFew studies to date have characterized functional connectivity (FC) within emotion and reward networks in relation to family dynamics in youth at high familial risk for bipolar disorder (HR-BD) and major depressive disorder (HR-MDD) relative to low-risk youth (LR). Such characterization may advance our understanding of the neural underpinnings of mood disorders and lead to more effective interventions.MethodsA total of 139 youth (43 HR-BD, 46 HR-MDD, and 50 LR) aged 12.9 ± 2.7 years were longitudinally followed for 4.5 ± 2.4 years. We characterized differences in striatolimbic FC that distinguished between HR-BD, HR-MDD, and LR and between resilience and conversion to psychopathology. We then examined whether risk status moderated FC-family dynamic associations. Finally, we examined whether baseline between-group FC differences predicted resilence versus conversion to psychopathology.ResultsHR-BD had greater amygdala-middle frontal gyrus and dorsal striatum-middle frontal gyrus FC relative to HR-MDD and LR, and HR-MDD had lower amygdala-fusiform gyrus and dorsal striatum-precentral gyrus FC relative to HR-BD and LR (voxel-level p < .001, cluster-level false discovery rate-corrected p < .05). Resilient youth had greater amygdala-orbitofrontal cortex and ventral striatum-dorsal anterior cingulate cortex FC relative to youth with conversion to psychopathology (voxel-level p < .001, cluster-level false discovery rate-corrected p < .05). Greater family rigidity was inversely associated with amygdala-fusiform gyrus FC across all groups (false discovery rate-corrected p = .017), with a moderating effect of bipolar risk status (HR-BD vs. HR-MDD p < .001; HR-BD vs. LR p = .005). Baseline FC differences did not predict resilence versus conversion to psychopathology.ConclusionsFindings represent neural signatures of risk and resilience in emotion and reward processing networks in youth at familial risk for mood disorders that may be targets for novel interventions tailored to the family context.