Research progress in the mechanism and prediction of suicide attempt in patients with depression

doi:10. 3969/ j. issn. 1006-7795. 2024. 01. 015

Abstract

Abstract: Suicide is the act of individuals intentionally or voluntarily taking various means to end their lives. The global annual suicide mortality rate is approximately 16/100 000,which means approximately 703 000 people die from suicide every year,making it the leading cause of death. Suicide often occurs in patients among which mental illness, among which the most common is depression. Studying the mechanism of suicidal behavior in depression can provide important data support for developing measares to prevent from suicidal ideation and suicidal behavior. The relevant factors for suicidal behavior include social,psychological,and biological factors. The article reviewed the advances related to suicidal behavior in magnetic resonance imaging,neurocognitive research,machine learning,ecological momentary assessment and digital phenotype,in order to provide reference for the development of early identification indicators for suicide risk.

Key words: suicide behavior, depression, mechanism

CLC Number:

R749

Ren Yanping, Wu Han, Wang Wen, Jin Wenqing, Li Rena. Research progress in the mechanism and prediction of suicide attempt in patients with depression[J]. Journal of Capital Medical University, doi: 10. 3969/ j. issn. 1006-7795. 2024. 01. 015.

References

［1］Bernert R A, Hilberg A M, Melia R, et al. Artificial intelligence and suicide prevention: a systematic review of machine learning investigations［J］. Int J Environ Res Public Health, 2020, 17(16): 5929.
［2］World Health Organization. Preventing suicide: a global imperative［EB/OL］. (2014-08-17)［2023-10-28］. https://www.who.int/publications/i/item/9789241564779.
［3］Coryell W, Fiedorowicz J, Solomon D, et al. Anxiety symptom severity and long-term risk for suicidal behavior in depressive disorders［J］. Suicide Life Threat Behav, 2019, 49(6): 1621-1629.
［4］Sokero T P, Melartin T K, Rytsälä H J, et al. Suicidal ideation and attempts among psychiatric patients with major depressive disorder［J］. J Clin Psychiatry, 2003, 64(9): 1094-1100.
［5］Dobbertin M, Blair K S, Carollo E, et al. Neuroimaging alterations of the suicidal brain and its relevance to practice: an updated review of MRI studies［J］. Front Psychiatry, 2023, 14: 1083244.
［6］Monkul E S, Hatch J P, Nicoletti M A, et al. Fronto-limbic brain structures in suicidal and non-suicidal female patients with major depressive disorder［J］. Mol Psychiatry, 2007, 12(4): 360-366.
［7］Ding Y, Lawrence N, Olié E, et al. Prefrontal cortex markers of suicidal vulnerability in mood disorders: a model-based structural neuroimaging study with a translational perspective［J］. Transl Psychiatry, 2015, 5(2): e516.
［8］Wagner G, Schultz C C, Koch K, et al. Prefrontal cortical thickness in depressed patients with high-risk for suicidal behavior［J］. J Psychiatr Res, 2012, 46(11): 1449-1455.
［9］Dixon M L, Thiruchselvam R, Todd R, et al. Emotion and the prefrontal cortex: an integrative review［J］. Psychol Bull, 2017, 143(10): 1033-1081.
［10］Mitchell D G V. The nexus between decision making and emotion regulation: a review of convergent neurocognitive substrates［J］. Behav Brain Res, 2011, 217(1): 215-231.
［11］Leyton M, Paquette V, Gravel P, et al. Alpha-［11C］Methyl-L-tryptophan trapping in the orbital and ventral medial prefrontal cortex of suicide attempters［J］. Eur Neuropsychopharmacol, 2006, 16(3): 220-223.
［12］Sullivan G M, Oquendo M A, Milak M, et al. Positron emission tomography quantification of serotonin(1A) receptor binding in suicide attempters with major depressive disorder［J］. JAMA Psychiatry, 2015, 72(2): 169-178.
［13］Goodman M, Hazlett E A, Avedon J B, et al. Anterior cingulate volume reduction in adolescents with borderline personality disorder and co-morbid major depression［J］. J Psychiatr Res, 2011, 45(6): 803-807.
［14］Oquendo M A, Placidi G P A, Malone K M, et al. Positron emission tomography of regional brainmetabolic responses to a serotonergic challenge and lethality of suicide attempts in major depression［J］. Arch Gen Psychiatry, 2003, 60(1): 14-22.
［15］Gosnell S N, Velasquez K M, Molfese D L, et al. Prefrontal cortex, temporal cortex, and hippocampus volume are affected in suicidal psychiatric patients［J］. Psychiatry Res Neuroimaging, 2016, 256: 50-56.
［16］Vang F J, Ryding E, Träskman-Bendz L, et al. Size of basal ganglia in suicide attempters, and its association with temperament and serotonin transporter density［J］. Psychiatry Res, 2010, 183(2): 177-179.
［17］Lee Y J, Kim S, Gwak A R, et al. Decreased regional gray matter volume in suicide attempters compared to suicide non-attempters with major depressive disorders［J］. Compr Psychiatry, 2016, 67: 59-65.
［18］Jia Z Y, Huang X Q, Wu Q Z, et al. High-field magnetic resonance imaging of suicidality in patients with major depressive disorder［J］. Am J Psychiatry, 2010, 167(11): 1381-1390.
［19］Jia Z Y, Wang Y Q, Huang X Q, et al. Impaired frontothalamic circuitry in suicidal patients with depression revealed by diffusion tensor imaging at 3.0 T［J］. J Psychiatry Neurosci, 2014, 39(3): 170-177.
［20］Wagner G, Koch K, Schachtzabel C, et al. Structural brain alterations in patients with major depressive disorder and high risk for suicide: evidence for a distinct neurobiological entity?［J］. Neuroimage, 2011, 54(2): 1607-1614.
［21］Wu H, Wang X, Wang D, et al. Abnormal fiber integrity in the cerebellum with recent suicide behavior in depressed patients: a diffusion tensor imaging study［J］. Asian J Psychiatr, 2023, 86: 103658.
［22］Cao J, Chen X R, Chen J M, et al. Resting-state functional MRI of abnormal baseline brain activity in young depressed patients with and without suicidal behavior［J］. J Affect Disord, 2016, 205: 252-263.
［23］Fan T T, Wu X, Yao L, et al. Abnormal baseline brain activity in suicidal and non-suicidal patients with major depressive disorder［J］. Neurosci Lett, 2013, 534: 35-40.
［24］Wagner G, Li M, Sacchet M D, et al. Functional network alterations differently associated with suicidal ideas and acts in depressed patients: an indirect support to the transition model［J］. Transl Psychiatry, 2021, 11(1): 100.
［25］Olié E, Ding Y, Le Bars E, et al. Processing of decision-making and social threat in patients with history of suicidal attempt: a neuroimaging replication study［J］. Psychiatry Res, 2015, 234(3): 369-377.
［26］Jollant F, Lawrence N S, Giampietro V, et al. Orbitofrontal cortex response to angry faces in men with histories of suicide attempts［J］. Am J Psychiatry, 2008, 165(6): 740-748.
［27］Pan L A, Hassel S, Segreti A M, et al. Differential patterns of activity and functional connectivity in emotion processing neural circuitry to angry and happy faces in adolescents with and without suicide attempt［J］. Psychol Med, 2013, 43(10): 2129-2142.
［28］Hagan C R, Joiner T E. The indirect effect of perceived criticism on suicide ideation and attempts［J］. Arch Suicide Res, 2017, 21(3): 438-454.
［29］Hames J L, Rogers M L, Silva C, et al. A social exclusion manipulation interacts with acquired capability for suicide to predict self-aggressive behaviors［J］. Arch Suicide Res, 2018, 22(1): 32-45.
［30］Gobbini M I, Haxby J V. Neural systems for recognition of familiar faces［J］. Neuropsychologia, 2007, 45(1): 32-41.
［31］Ida Gobbini M, Leibenluft E, Santiago N, et al. Social and emotional attachment in the neural representation of faces［J］. Neuroimage, 2004, 22(4): 1628-1635.
［32］Palermo R, Rhodes G. Are you always on my mind? A review of how face perception and attention interact［J］. Neuropsychologia, 2007, 45(1): 75-92.
［33］Johnson M H, Griffin R, Csibra G, et al. The emergence of the social brain network: evidence from typical and atypical development［J］. Dev Psychopathol, 2005, 17(3): 599-619.
［34］Reisch T, Seifritz E, Esposito F, et al. An fMRI study on mental pain and suicidal behavior［J］. J Affect Disord, 2010, 126(1/2): 321-325.
［35］Dombrovski A Y, Szanto K, Clark L, et al. Reward signals, attempted suicide, and impulsivity in late-life depression［J］. JAMA Psychiatry, 2013, 70(10): 1.
［36］Spreng R N, Mar R A, Kim A S N. The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: a quantitative meta-analysis［J］. J Cogn Neurosci, 2009, 21(3): 489-510.
［37］Schacter D L, Addis D R, Buckner R L. Remembering the past to imagine the future: the prospective brain［J］. Nat Rev Neurosci, 2007, 8(9): 657-661.
［38］Peters J, Büchel C. Episodic future thinking reduces reward delay discounting through an enhancement of prefrontal-mediotemporal interactions［J］. Neuron, 2010, 66(1): 138-148.
［39］Nock M K, Banaji M R. Assessment of self-injurious thoughts using a behavioral test［J］. Am J Psychiatry, 2007, 164(5): 820-823.
［40］Nock M K, Park J M, Finn C T, et al. Measuring the suicidal mind: implicit cognition predicts suicidal behavior［J］. Psychol Sci, 2010, 21(4): 511-517.
［41］Randall J R, Rowe B H, Dong K A, et al. Assessment of self-harm risk using implicit thoughts［J］. Psychol Assess, 2013, 25(3): 714-721.
［42］Barnes S M, Bahraini N H, Forster J E, et al. Moving beyond self-report: implicit associations about death/life prospectively predict suicidal behavior among veterans［J］. Suicide Life Threat Behav, 2017, 47(1): 67-77.
［43］Tello N, Harika-Germaneau G, Serra W, et al. Forecasting a fatal decision: direct replication of the predictive validity of the suicide-implicit association test［J］. Psychol Sci, 2020, 31(1): 65-74.
［44］Ballard E D, Reed J L, Szczepanik J, et al. Functional imaging of the implicit association of the self with life and death［J］. Suicide Life Threat Behav, 2019, 49(6): 1600-1608.
［45］Ballard E D, Gilbert J R, Fields J S, et al. Network changes in insula and amygdala connectivity accompany implicit suicidal associations［J］. Front Psychiatry, 2020, 11: 577628.
［46］Bryan C J, Bryan A O. Delayed reward discounting and increased risk for suicide attempts among U.S. adults with probable PTSD［J］. J Anxiety Disord, 2021, 81: 102414.
［47］Chu C, Hammock E A D, Joiner T E. Unextracted plasma oxytocin levels decrease following in-laboratory social exclusion in young adults with a suicide attempt history［J］. J Psychiatr Res, 2020, 121: 173-181.
［48］Gilbert J R, Gerner J L, Burton C R, et al. Magnetoencephalography biomarkers of suicide attempt history and antidepressant response to ketamine in treatment-resistant major depression［J］. J Affect Disord, 2022, 312: 188-197.
［49］Richard-Devantoy S, Ding Y, Lepage M, et al. Cognitive inhibition in depression and suicidal behavior: a neuroimaging study［J］. Psychol Med, 2016, 46(5): 933-944.
［50］Meyer I H, Dietrich J, Schwartz S. Lifetime prevalence of mental disorders and suicide attempts in diverse lesbian, gay, and bisexual populations［J］. Am J Public Health, 2008, 98(6): 1004-1006.
［51］Interian A, Myers C E, Chesin M S, et al. Towards the objective assessment of suicidal states: some neurocognitive deficits may be temporally related to suicide attempt［J］. Psychiatry Res, 2020, 287: 112624.
［52］Mccoy K, Fremouw W, Mcneil D W. Thresholds and tolerance of physical pain among young adults who self-injure［J］. Pain Res Manag, 2010, 15(6): 371-377.
［53］Rabasco A, Andover M S. The interaction of dissociation,pain tolerance,and suicidal ideation in predicting suicide attempts［J］. Psychiatry Res, 2020, 284: 112661.
［54］Orbach I, Stein D, Palgi Y, et al. Perception of physical pain in accident and suicide attempt patients: self-preservation vs self-destruction［J］. J Psychiatr Res, 1996, 30(4): 307-320.
［55］Hazlett E A, Blair N J, Fernandez N, et al. Startle amplitude during unpleasant pictures is greater in veterans with a history of multiple-suicide attempts and predicts a future suicide attempt［J］. Psychophysiology, 2016, 53(10): 1524-1534.
［56］Ballard E D, Ionescu D F, Vande Voort J L, et al. Increased fear-potentiated startle in major depressive disorder patients with lifetime history of suicide attempt［J］. J Affect Disord, 2014, 162: 34-38.
［57］Alacreu-Crespo A, Guillaume S, Sénèque M, et al. Cognitive modelling to assess decision-making impairments in patients with current depression and with/without suicide history［J］. Eur Neuropsychopharmacol, 2020, 36: 50-59.
［58］Richard-Devantoy S, Ding Y, Turecki G, et al. Attentional bias toward suicide-relevant information in suicide attempters: a cross-sectional study and a meta-analysis［J］. J Affect Disord, 2016, 196: 101-108.
［59］Franklin J C, Ribeiro J D, Fox K R, et al. Risk factors for suicidal thoughts and behaviors: a meta-analysis of 50 years of research［J］. Psychol Bull, 2017, 143(2): 187-232.
［60］况利, 徐小明, 曾琪. 机器学习用于自杀研究的综述［J］. 山东大学学报: 医学版, 2022, 60(4): 10-16.
［61］Carson N J, Mullin B, Sanchez M J, et al. Identification of suicidal behavior among psychiatrically hospitalized adolescents using natural language processing and machine learning of electronic health records［J］. PLoS One, 2019, 14(2): e0211116.
［62］Walsh C G, Ribeiro J D, Franklin J C. Predicting suicide attempts in adolescents with longitudinal clinical data and machine learning［J］. J Child Psychol Psychiatry, 2018, 59(12): 1261-1270.
［63］Miché M, Studerus E, Meyer A H, et al. Prospective prediction of suicide attempts in community adolescents and young adults, using regression methods and machine learning［J］. J Affect Disord, 2020, 265: 570-578.
［64］Jung J S, Park S J, Kim E Y, et al. Prediction models for high risk of suicide in Korean adolescents using machine learning techniques［J］. PLoS One, 2019, 14(6): e0217639.
［65］Bae S M, Lee S A, Lee S H. Prediction by data mining, of suicide attempts in Korean adolescents: a national study［J］. Neuropsychiatr Dis Treat, 2015, 11: 2367-2375.
［66］Kessler R C, Stein M B, Petukhova M V, et al. Predicting suicides after outpatient mental health visits in the army study to assess risk and resilience in servicemembers (Army STARRS)［J］. Mol Psychiatry, 2017, 22(4): 544-551.
［67］Parsaei M, Taghavizanjani F, Cattarinussi G, et al. Classification of suicidality by training supervised machine learning models with brain MRI findings: a systematic review［J］. J Affect Disord, 2023, 340: 766-791.
［68］Burke T A, Jacobucci R, Ammerman B A, et al. Using machine learning to classify suicide attempthistory among youth in medical care settings［J］. J Affect Disord, 2020, 268: 206-214.
［69］Ballard E D, Gilbert J R, Wusinich C, et al. New methods for assessing rapid changes in suicide risk［J］. Front Psychiatry, 2021, 12: 598434.
［70］Husky M, Swendsen J, Ionita A, et al. Predictors of daily life suicidal ideation in adults recently discharged after a serious suicide attempt: a pilot study［J］. Psychiatry Res, 2017, 256: 79-84.
［71］Gratch I, Choo T H, Galfalvy H, et al. Detecting suicidal thoughts: the power of ecological momentary assessment［J］. Depress Anxiety, 2021, 38(1): 8-16.
［72］KleimanE M, Turner B J, Fedor S, et al. Examination of real-time fluctuations in suicidal ideation and its risk factors: results from two ecological momentary assessment studies［J］. J Abnorm Psychol, 2017, 126(6): 726-738.
［73］Littlewood D L, Kyle S D, Carter L A, et al. Short sleep duration and poor sleep quality predict next-day suicidal ideation: an ecological momentary assessment study［J］. Psychol Med, 2019, 49(3): 403-411.
［74］Rath D, de Beurs D, Hallensleben N, et al. Modelling suicide ideation from beep to beep: application of network analysis to ecological momentary assessment data［J］. Internet Interv, 2019, 18: 100292.
［75］Peis I, Olmos P M, Vera-Varela C, et al. Deep sequential models for suicidal ideation from multiple source data［J］. IEEE J Biomed Health Inform, 2019, 23(6): 2286-2293.
［76］Jacobson N C, Feng B. Digital phenotyping of generalized anxiety disorder: using artificial intelligence to accurately predict symptom severity using wearable sensors in daily life［J］. Transl Psychiatry, 2022, 12(1): 336.
［77］Kleiman E M, Turner B J, Fedor S, et al. Digital phenotyping of suicidal thoughts［J］. Depress Anxiety, 2018, 35(7): 601-608.
［78］Henson P, Torous J. Feasibility and correlations of smartphone meta-data toward dynamic understanding of depression and suicide risk in schizophrenia［J］. Int J Methods Psychiatr Res, 2020, 29(2): e1825.
［79］Mikus A, Hoogendoorn M, Rocha A, et al. Predicting short term mood developments among depressed patients using adherence and ecological momentary assessment data［J］. Internet Interv, 2018, 12: 105-110.
［80］Mohr D C, Zhang M, Schueller S M. Personal sensing:understanding mental health using ubiquitous sensors and machine learning［J］. Annu Rev Clin Psychol, 2017, 13: 23-47.
［81］Low D M, Rumker L, Talkar T, et al. Natural language processing reveals vulnerable mental health support groups and heightened health anxiety on reddit during covid-19: observational study［J］. J Med Internet Res, 2020, 22(10): e22635.
［82］Berrouiguet S, Barrigón M L, Castroman J L, et al. Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol［J］. BMC Psychiatry, 2019, 19(1): 277.
［83］Kleiman E M, Glenn C R, Liu R T. Real-time monitoring of suicide risk among adolescents: potential barriers, possible solutions, and future directions［J］. J Clin Child Adolesc Psychol, 2019, 48(6): 934-946.
［84］Porras-Segovia A, Molina-Madueo R M, Berrouiguet S, et al. Smartphone-based ecological momentary assessment (EMA) in psychiatric patients and student controls: A real-world feasibility study［J］. J Affect Disord, 2020, 274: 733-741.

[1]	Wu Ziyao, Feng Sitong, Dong Linrui, Zheng Sisi, Ning Yanzhe, Jia Hongxiao. Study of cognitive function and social function in the subhealthy people with spleen qi deficiency syndrome [J]. Journal of Capital Medical University, 2024, 45(3): 453-457.
[2]	Dai Zhiqing, Lin Jin, Duan Yuhang, Teng Fei, Lyu Hongpeng, Jia Hongxiao. A study on the differences of cognitive functions between individuals dominated by Wood Element and Metal Element among the Five Elements people [J]. Journal of Capital Medical University, 2024, 45(3): 458-465.
[3]	Teng Fei, Song Mingkang, Lyu Hongpeng, Jia Hongxiao. Research progresses on the correlation between personality traits and cognitive function [J]. Journal of Capital Medical University, 2024, 45(3): 466-471.
[4]	Guan Le, Song Tianbin, Hou Yaqin, Li Ze, Yan Shaozhen, Zhang Chun. The value of qualitative and semi-quantitative analysis of ¹¹C-PIB PET in the differential diagnosis of Alzheimer's disease [J]. Journal of Capital Medical University, 2024, 45(1): 19-24.
[5]	Xu Jinjie, Wang Meiti, Wang Chengrui, Jin Wenqing, Ren Yanping, Wang Wei. Study on the correlation between suicide in patients with bipolar disorder depressive episodes and IgA [J]. Journal of Capital Medical University, 2024, 45(1): 52-60.
[6]	Wu Han, Wang Xue, Wang Dan, Wang Wen, Jin Wenqing, Jiang Wei, Ren Yanping. Impact of cognitive function on suicidal behavior in patients with depressive episodes [J]. Journal of Capital Medical University, 2024, 45(1): 61-67.
[7]	Wang Dan, Wang Xue, Wu Han, Jin Wenqing, Wang Wen, Ren Yanping. Relationship of HPA axis and HPT axis impairment with suicide attempts in non-suicidal self-injury adolescents [J]. Journal of Capital Medical University, 2024, 45(1): 68-74.
[8]	Zhu Dandi, Pan Weigang, Lian Siyuan, Guo Tong, Mao Peixian, Chen Xueyan. Factors associated with risk of suicide in late life depression [J]. Journal of Capital Medical University, 2024, 45(1): 75-80.
[9]	Yuan Xiaofei, Liu Mengqi, Wu Yuanzhen, Tian Yin, Ren Yanping, Chen Xu. The influencing factor analysis of attempted suicide in adolescent patients with mood disorders [J]. Journal of Capital Medical University, 2024, 45(1): 81-87.
[10]	Duan Yuhang, Lyu Hongpeng, Teng Fei, Dai Zhiqing, Lin Jin, Jia Hongxiao. A comparative study on the differences in cognitive functions between Fire Element and Water Element among the Five Element people [J]. Journal of Capital Medical University, 2024, 45(1): 111-117.
[11]	Li Zhiheng, Yu Xin, Yuan Ying, Xu Zhiqing. mpact of prenatal stress on evoked expression of c-Fos in emotion-related brain areas [J]. Journal of Capital Medical University, 2023, 44(6): 1014-1021.
[12]	Zhang Ying, Wang Ruomei, Li Gang, Li Lusha. The effects of comprehensive psychological intervention on executive and social functioning in stable schizophrenic patients [J]. Journal of Capital Medical University, 2023, 44(5): 859-864.
[13]	Li Xue, Feng Zhengtian, Zheng Sisi, Duan Yuhang, Wu Ziyao, Zhu Hong, Jia Hongxiao. Network analysis of mental and physical symptoms in patients with generalized anxiety disorder [J]. Journal of Capital Medical University, 2023, 44(4): 568-577.
[14]	Song Mingkang, Xu Tianchao, Jia Hongxiao, Li Dongdong, Zheng Sisi, Yin Dongqing, Li Xue. Exploration of traditional Chinese medicine syndrome discipline of panic disorder based on Cluster analysis and Bayesian network [J]. Journal of Capital Medical University, 2023, 44(4): 583-589.
[15]	Zhong Jie, Zhu Hong, Hao Jun, Jia Hongxiao. The mediating effect of theory of mind between psychotic symptoms and social functioning in stable schizophrenia [J]. Journal of Capital Medical University, 2023, 44(4): 590-595.