Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

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.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: PCC-ACC functional connectivity as a function of Family History.
Fig. 2

References

  1. 1.

    Ferrari AJ, Somerville AJ, Baxter AJ, Norman R, Patten SB, Vos T, et al. Global variation in the prevalence and incidence of major depressive disorder: a systematic review of the epidemiological literature. Psychol Med. 2013;43:471–81.

    CAS  PubMed  Article  Google Scholar 

  2. 2.

    Mykletun A, Bjerkeset O, Dewey M, Prince M, Overland S, Stewart R. Anxiety, depression, and cause-specific mortality: the HUNT study. Psychosom Med. 2007;69:323–31.

    PubMed  Article  Google Scholar 

  3. 3.

    Hawton K, Casanas ICC, Haw C, Saunders K. Risk factors for suicide in individuals with depression: a systematic review. J Affect Disord. 2013;147:17–28.

    PubMed  Article  Google Scholar 

  4. 4.

    Keren H, O’Callaghan G, Vidal-Ribas P, Buzzell GA, Brotman MA, Leibenluft E, et al. Reward processing in depression: a conceptual and meta-analytic review across fMRI and EEG studies. Am J Psychiatry. 2018;175:1111–20.

    PubMed  PubMed Central  Article  Google Scholar 

  5. 5.

    Auerbach RP, Pagliaccio D, Allison GO, Alqueza KL, Alonso MF. Neural Correlates Associated With Suicide and Nonsuicidal Self-injury in Youth. Biol Psychiatry. 2021;89:119–33.

  6. 6.

    Schmaal L, van Harmelen AL, Chatzi V, Lippard ETC, Toenders YJ, Averill LA, et al. Imaging suicidal thoughts and behaviors: a comprehensive review of 2 decades of neuroimaging studies. Mol Psychiatry. 2020;25:408–27.

    PubMed  Article  Google Scholar 

  7. 7.

    Huang X, Rootes-Murdy K, Bastidas DM, Nee DE, Franklin JC. Brain differences associated with self-injurious thoughts and behaviors: a meta-analysis of neuroimaging studies. Sci Rep. 2020;10:2404.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  8. 8.

    Janiri D, Moser DA, Doucet GE, Luber MJ, Rasgon A, Lee WH, et al. Shared neural phenotypes for mood and anxiety disorders: a meta-analysis of 226 task-related functional imaging studies. JAMA Psychiatry. 2020;77:172–9.

  9. 9.

    Chase HW, Segreti AM, Keller TA, Cherkassky VL, Just MA, Pan LA, et al. Alterations of functional connectivity and intrinsic activity within the cingulate cortex of suicidal ideators. J Affect Disord. 2017;212:78–85.

    PubMed  PubMed Central  Article  Google Scholar 

  10. 10.

    Malhi GS, Das P, Outhred T, Bryant RA, Calhoun V, Mann JJ. Default mode dysfunction underpins suicidal activity in mood disorders. Psychol Med. 2020;50:1214–23.

    PubMed  Article  Google Scholar 

  11. 11.

    Ordaz SJ, Goyer MS, Ho TC, Singh MK, Gotlib IH. Network basis of suicidal ideation in depressed adolescents. J Affect Disord. 2018;226:92–99.

    PubMed  Article  Google Scholar 

  12. 12.

    Drysdale AT, Grosenick L, Downar J, Dunlop K, Mansouri F, Meng Y, et al. Resting-state connectivity biomarkers define neurophysiological subtypes of depression. Nat Med. 2017;23:28–38.

    CAS  PubMed  Article  Google Scholar 

  13. 13.

    Mulders PC, van Eijndhoven PF, Schene AH, Beckmann CF, Tendolkar I. Resting-state functional connectivity in major depressive disorder: a review. Neurosci Biobehav Rev. 2015;56:330–44.

    PubMed  Article  Google Scholar 

  14. 14.

    Raichle ME, MacLeod AM, Snyder AZ, Powers WJ, Gusnard DA, Shulman GL. A default mode of brain function. Proc Natl Acad Sci USA. 2001;98:676–82.

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Hamilton JP, Farmer M, Fogelman P, Gotlib IH. Depressive rumination, the default-mode network, and the dark matter of clinical neuroscience. Biol Psychiatry. 2015;78:224–30.

    PubMed  PubMed Central  Article  Google Scholar 

  16. 16.

    Posner J, Cha J, Wang Z, Talati A, Warner V, Gerber A, et al. Increased default mode network connectivity in individuals at high familial risk for depression. Neuropsychopharmacology. 2016;41:1759–67.

    CAS  PubMed  Article  Google Scholar 

  17. 17.

    Chai XJ, Hirshfeld-Becker D, Biederman J, Uchida M, Doehrmann O, Leonard JA, et al. Altered intrinsic functional brain architecture in children at familial risk of major depression. Biol Psychiatry. 2016;80:849–58.

    PubMed  Article  Google Scholar 

  18. 18.

    Berman MG, Peltier S, Nee DE, Kross E, Deldin PJ, Jonides J. Depression, rumination and the default network. Soc Cogn Affect Neurosci. 2011;6:548–55.

    PubMed  Article  Google Scholar 

  19. 19.

    Zhang S, Chen JM, Kuang L, Cao J, Zhang H, Ai M, et al. Association between abnormal default mode network activity and suicidality in depressed adolescents. BMC Psychiatry. 2016;16:337.

    PubMed  PubMed Central  Article  Google Scholar 

  20. 20.

    Miranda R, Nolen-Hoeksema S. Brooding and reflection: rumination predicts suicidal ideation at 1-year follow-up in a community sample. Behav Res Ther. 2007;45:3088–95.

    PubMed  PubMed Central  Article  Google Scholar 

  21. 21.

    Leech R, Kamourieh S, Beckmann CF, Sharp DJ. Fractionating the default mode network: distinct contributions of the ventral and dorsal posterior cingulate cortex to cognitive control. J Neurosci. 2011;31:3217–24.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. 22.

    Menon V. Large-scale brain networks and psychopathology: a unifying triple network model. Trends Cogn Sci. 2011;15:483–506.

    PubMed  Article  Google Scholar 

  23. 23.

    Schwartz J, Ordaz SJ, Ho TC, Gotlib IH. Longitudinal decreases in suicidal ideation are associated with increases in salience network coherence in depressed adolescents. J Affect Disord. 2019;245:545–52.

    PubMed  Article  Google Scholar 

  24. 24.

    Zuo XN, Di Martino A, Kelly C, Shehzad ZE, Gee DG, Klein DF, et al. The oscillating brain: complex and reliable. Neuroimage. 2010;49:1432–45.

    PubMed  Article  Google Scholar 

  25. 25.

    Mennes M, Zuo XN, Kelly C, Di Martino A, Zang YF, Biswal B, et al. Linking inter-individual differences in neural activation and behavior to intrinsic brain dynamics. Neuroimage. 2011;54:2950–9.

    PubMed  Article  Google Scholar 

  26. 26.

    Auer DP. Spontaneous low-frequency blood oxygenation level-dependent fluctuations and functional connectivity analysis of the ‘resting’ brain. Magn Reson Imaging. 2008;26:1055–64.

    PubMed  Article  Google Scholar 

  27. 27.

    Baria AT, Baliki MN, Parrish T, Apkarian AV. Anatomical and functional assemblies of brain BOLD oscillations. J Neurosci. 2011;31:7910–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. 28.

    Weissman MM, Wickramaratne P, Gameroff MJ, Warner V, Pilowsky D, Kohad RG, et al. Offspring of depressed parents: 30 years later. Am J Psychiatry. 2016;173:1024–32.

    PubMed  Article  Google Scholar 

  29. 29.

    Weissman MM, Berry OO, Warner V, Gameroff MJ, Skipper J, Talati A, et al. A 30-year study of 3 generations at high risk and low risk for depression. JAMA Psychiatry. 2016;73:970–7.

    PubMed  PubMed Central  Article  Google Scholar 

  30. 30.

    Warner V, Wickramaratne P, Weissman MM. The role of fear and anxiety in the familial risk for major depression: a three-generation study. Psychol Med. 2008;38:1543–56.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    Weissman MM, Wickramaratne P, Nomura Y, Warner V, Verdeli H, Pilowsky DJ, et al. Families at high and low risk for depression: a 3-generation study. Arch Gen Psychiatry. 2005;62:29–36.

    PubMed  Article  Google Scholar 

  32. 32.

    Arnett JJ. Emerging adulthood: the winding road from the late teens through the twenties. Oxford University Press; 2014.

  33. 33.

    Mannuzza S, Fyer AJ, Klein DF, Endicott J. Schedule for affective disorders and schizophrenia-lifetime version modified for the study of anxiety disorders (SADS-LA): rationale and conceptual development. J Psychiatr Res. 1986;20:317–25.

    CAS  PubMed  Article  Google Scholar 

  34. 34.

    Kaufman J, Birmaher B, Brent D, Rao U, Flynn C, Moreci P, et al. Schedule for affective disorders and schizophrenia for school-age children-present and lifetime version (K-SADS-PL): initial reliability and validity data. J Am Acad Child Adolesc Psychiatry. 1997;36:980–8.

    CAS  PubMed  Article  Google Scholar 

  35. 35.

    Leckman JF, Sholomskas D, Thompson WD, Belanger A, Weissman MM. Best estimate of lifetime psychiatric diagnosis: a methodological study. Arch Gen Psychiatry. 1982;39:879–83.

    CAS  PubMed  Article  Google Scholar 

  36. 36.

    Hamilton M. Development of a rating scale for primary depressive illness. Br J Soc Clin Psychol. 1967;6:278–96.

    CAS  PubMed  Article  Google Scholar 

  37. 37.

    Belleau EL, Kremens R, Ang YS, Pisoni A, Bondy E, Durham K, et al. Reward functioning abnormalities in adolescents at high familial risk for depressive disorders. Biol Psychiatry Cogn Neurosci Neuroimaging. 2021;6:270–9.

  38. 38.

    Gorgolewski K, Burns CD, Madison C, Clark D, Halchenko YO, Waskom ML, et al. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python. Front Neuroinform. 2011;5:13.

    PubMed  PubMed Central  Article  Google Scholar 

  39. 39.

    Behzadi Y, Restom K, Liau J, Liu TT. A component based noise correction method (CompCor) for BOLD and perfusion based fMRI. Neuroimage. 2007;37:90–101.

    PubMed  PubMed Central  Article  Google Scholar 

  40. 40.

    Beckmann M, Johansen-Berg H, Rushworth MF. Connectivity-based parcellation of human cingulate cortex and its relation to functional specialization. J Neurosci. 2009;29:1175–90.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. 41.

    Costello EJ, Pine DS, Hammen C, March JS, Plotsky PM, Weissman MM, et al. Development and natural history of mood disorders. Biol Psychiatry. 2002;52:529–42.

    PubMed  Article  PubMed Central  Google Scholar 

  42. 42.

    Weissman MM, Wickramaratne P, Nomura Y, Warner V, Pilowsky D, Verdeli H. Offspring of depressed parents: 20 years later. Am J Psychiatry. 2006;163:1001–8.

    PubMed  Article  PubMed Central  Google Scholar 

  43. 43.

    Watson D, Clark LA, Chmielewski M, Kotov R. The value of suppressor effects in explicating the construct validity of symptom measures. Psychol Assess. 2013;25:929–41.

    PubMed  PubMed Central  Article  Google Scholar 

  44. 44.

    Milne BJ, Caspi A, Harrington H, Poulton R, Rutter M, Moffitt TE. Predictive value of family history on severity of illness: the case for depression, anxiety, alcohol dependence, and drug dependence. Arch Gen Psychiatry. 2009;66:738–47.

    PubMed  PubMed Central  Article  Google Scholar 

  45. 45.

    Talati A, Weissman MM, Hamilton SP. Using the high-risk family design to identify biomarkers for major depression. Philos Trans R Soc Lond B Biol Sci. 2013;368:20120129.

    PubMed  PubMed Central  Article  Google Scholar 

  46. 46.

    Hao X, Talati A, Shankman SA, Liu J, Kaiser J, Tenke CE, et al. Stability of cortical thinning in persons at increased familial risk for major depressive disorder across 8 years. Biol Psychiatry Cogn Neurosci Neuroimaging. 2017;2:619–25.

    PubMed  PubMed Central  Google Scholar 

  47. 47.

    Kuhn S, Vanderhasselt MA, De Raedt R, Gallinat J. Why ruminators won’t stop: the structural and resting state correlates of rumination and its relation to depression. J Affect Disord. 2012;141:352–60.

    PubMed  Article  Google Scholar 

  48. 48.

    Makovac E, Fagioli S, Rae CL, Critchley HD, Ottaviani C. Can’t get it off my brain: meta-analysis of neuroimaging studies on perseverative cognition. Psychiatry Res Neuroimaging. 2020;295:111020.

    PubMed  Article  Google Scholar 

  49. 49.

    Lan MJ, Rizk MM, Pantazatos SP, Rubin-Falcone H, Miller JM, Sublette ME, et al. Resting-state amplitude of low-frequency fluctuation is associated with suicidal ideation. Depress Anxiety. 2019;36:433–41.

    PubMed  PubMed Central  Article  Google Scholar 

  50. 50.

    Seitzman BA, Gratton C, Laumann TO, Gordon EM, Adeyemo B, Dworetsky A, et al. Trait-like variants in human functional brain networks. Proc Natl Acad Sci USA. 2019;116:22851–61.

    CAS  PubMed  Article  Google Scholar 

  51. 51.

    Braga RM, Buckner RL. Parallel interdigitated distributed networks within the individual estimated by intrinsic functional connectivity. Neuron. 2017;95:457–71. e5.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. 52.

    Bzdok D, Heeger A, Langner R, Laird AR, Fox PT, Palomero-Gallagher N, et al. Subspecialization in the human posterior medial cortex. Neuroimage. 2015;106:55–71.

    PubMed  Article  Google Scholar 

  53. 53.

    Bauer CCC, Okano K, Ghosh SS, Lee YJ, Melero H, Angeles CL, et al. Real-time fMRI neurofeedback reduces auditory hallucinations and modulates resting state connectivity of involved brain regions: Part 2: Default mode network -preliminary evidence. Psychiatry Res. 2020;284:112770.

    PubMed  PubMed Central  Article  Google Scholar 

  54. 54.

    Rush AJ, First MB, Blacker D, American Psychiatric Association. Task force for the handbook of psychiatric measures. Handbook of psychiatric measures. 2nd ed. Washington, DC: American Psychiatric Publication; 2008.

  55. 55.

    Posner K, Brown GK, Stanley B, Brent DA, Yershova KV, Oquendo MA, et al. The Columbia-Suicide Severity Rating Scale: initial validity and internal consistency findings from three multisite studies with adolescents and adults. Am J Psychiatry. 2011;168:1266–77.

    PubMed  PubMed Central  Article  Google Scholar 

  56. 56.

    Nock MK, Holmberg EB, Photos VI, Michel BD. Self-injurious thoughts and behaviors interview: development, reliability, and validity in an adolescent sample. Psychol Assess. 2007;19:309–17.

    PubMed  Article  Google Scholar 

  57. 57.

    Birn RM, Molloy EK, Patriat R, Parker T, Meier TB, Kirk GR, et al. The effect of scan length on the reliability of resting-state fMRI connectivity estimates. Neuroimage. 2013;83:550–8.

    PubMed  PubMed Central  Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Ardesheer Talati.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chase, H.W., Auerbach, R.P., Brent, D.A. et al. Dissociating default mode network resting state markers of suicide from familial risk factors for depression. Neuropsychopharmacol. (2021). https://doi.org/10.1038/s41386-021-01022-5

Download citation

Search

Quick links