Dissociating default mode network resting state markers of suicide from familial risk factors for depression

Abstract

Neural signatures of suicide risk likely reflect a combination of specific and non-specific factors, and clarifying specific factors may facilitate development of novel treatments. Previously, we demonstrated an altered pattern of resting state connectivity between the dorsal and ventral posterior cingulate cortex (d/vPCC) and the dorsal anterior cingulate cortex (dACC), as well as altered low frequency oscillations in these regions, in individuals with a history of suicidal thoughts and behaviors (STBs) compared to healthy controls. It remains uncertain, however, whether these markers were directly related to STBs or, more generally, reflect a trait-level risk factor for depression. Here, we examined data from a 3-generational longitudinal study of depression where resting state fMRI data were analyzed from 2nd and 3rd generation offspring of probands with (FH+ = 44: STB+ = 32, STB- = 12) and without (FH- = 25: STB+ = 15, STB- = 10) a family history of major depressive disorder (MDD). Standard seed-based methods and a frequency-based analysis of intrinsic neural activity (ALFF/fALFF) were employed. FH of MDD, but not a personal history of STBs or MDD, was associated with relatively reduced dPCC-dACC, and enhanced vPCC-dACC functional connectivity. FH of MDD showed a pattern of reduced ALFF in the dPCC whereas an STB history was associated with an increase. All findings were invariant to confounding by lifetime MDD and current depression severity. Overall, contrary to predictions, resting state functional connectivity within the default mode network (DMN) was associated with FH of depression rather than STBs. These findings confirm the relevance of DMN functional connectivity for mood disorders and underscore the importance of disambiguating biological factors that differentially relate to mental disorders versus STBs.

Fig. 1. PCC-ACC functional connectivity as a function of Family History.

A PCC-ACC functional connectivity, split by FH, from the present study (filtered data). B PCC-ACC functional connectivity, split by FH, from the present study (unfiltered data).

Fig. 2

ALFF values within dPCC, vPCC and dACC regions of interest.