Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide

Molecular Psychiatry

Volumn 25, Issue 10, 2020, Pages 2422-2430

  Ruderfer, Douglas M ^a   Walsh, Colin G ^a   Aguirre, Matthew W ^b   Tanigawa, Yosuke ^b   Ribeiro, Jessica D ^c   Franklin, Joseph C ^c   Rivas, Manuel A ^b  

^a VANDERBILT UNIVERSITY MEDICAL CENTER   (United States)

^b STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c FLORIDA STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; CONTROLLED STUDY; ELECTRONIC HEALTH RECORD; FEMALE; GENETIC CORRELATION; GENETIC RISK SCORE; GENETIC VARIATION; GENOME-WIDE ASSOCIATION STUDY; GENOTYPE; HERITABILITY; HUMAN; INSOMNIA; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; MIDDLE AGED; PATIENT-REPORTED OUTCOME; PHENOTYPE; PREDICTION; PRIORITY JOURNAL; RISK; SINGLE NUCLEOTIDE POLYMORPHISM; SUICIDE ATTEMPT; UNITED KINGDOM; BIOBANK; CAUCASIAN; GENETICS; HEALTH SURVEY; MENTAL HEALTH; PROBABILITY; RISK FACTOR; SUICIDAL IDEATION; TENNESSEE;

BIOLOGICAL SPECIMEN BANKS; ELECTRONIC HEALTH RECORDS; EUROPEAN CONTINENTAL ANCESTRY GROUP; FEMALE; GENOME-WIDE ASSOCIATION STUDY; HEALTH SURVEYS; HUMANS; MACHINE LEARNING; MALE; MENTAL HEALTH; PHENOTYPE; PROBABILITY; RISK FACTORS; SUICIDAL IDEATION; SUICIDE, ATTEMPTED; TENNESSEE; UNITED KINGDOM;

EID: 85059579821     PISSN: 13594184     EISSN: 14765578     Source Type: Journal    
DOI: 10.1038/s41380-018-0326-8     Document Type: Article

References (42)

1. WHO. Suicide data. 2018. http://www.who.int/mental_health/prevention/suicide/suicideprevent/en/. (accessed 3 January 2018).
2. CDC (Centers for Disease Control and Prevention). Statistics|Suicide|Violence Prevention|Injury Center. 2018. https://www.cdc.gov/violenceprevention/suicide/statistics/. (accessed 3 January 2018).
3. CDC (Centers for Disease Control and Prevention). Suicidal thoughts and behaviors among adults aged ≥ 18 years—United States, 2008–2009. 2018. https://www.cdc.gov/mmwr/preview/mmwrhtml/ss6013a1.htm. (accessed 3 January 2018).
4. Nock MK, Borges G, Bromet EJ, Cha CB, Kessler RC, Lee S. Suicide and suicidal behavior. Epidemiol Rev. 2008;30:133–54. DOI: 10.1093/epirev/mxn002
5. Olfson M, Blanco C, Wall M, Liu S-M, Saha TD, Pickering RP, et al. National trends in suicide attempts among adults in the United States. JAMA Psychiatry. 2017;74:1095–103. DOI: 10.1001/jamapsychiatry.2017.2582
6. Statham DJ, Heath AC, Madden PA, Bucholz KK, Bierut L, Dinwiddie SH, et al. Suicidal behaviour: an epidemiological and genetic study. Psychol Med. 1998;28:839–55. DOI: 10.1017/S0033291798006916
7. Roy A, Segal NL. Suicidal behavior in twins: a replication. J Affect Disord. 2001;66:71–4. DOI: 10.1016/S0165-0327(00)00275-5
8. Sokolowski M, Wasserman J, Wasserman D. Genome-wide association studies of suicidal behaviors: a review. Eur Neuropsychopharmacol. 2014;24:1567–77. DOI: 10.1016/j.euroneuro.2014.08.006
9. Voracek M, Loibl LM. Genetics of suicide: a systematic review of twin studies. Wien Klin Wochenschr. 2007;119:463–75. DOI: 10.1007/s00508-007-0823-2
10. Perlis RH, Huang J, Purcell S, Fava M, Rush AJ, Sullivan PF, et al. Genome-wide association study of suicide attempts in mood disorder patients. Am J Psychiatry. 2010;167:1499–507. DOI: 10.1176/appi.ajp.2010.10040541
11. Stein MB, Ware EB, Mitchell C, Chen C-Y, Borja S, Cai T, et al. Genomewide association studies of suicide attempts in US soldiers. Am J Med Genet B Neuropsychiatr Genet. 2017;174:786–97. n/a-n/a DOI: 10.1002/ajmg.b.32594
12. Willour VL, Seifuddin F, Mahon PB, Jancic D, Pirooznia M, Steele J, et al. A genome-wide association study of attempted suicide. Mol Psychiatry. 2012;17:433. DOI: 10.1038/mp.2011.4
13. Zai CC, Gonçalves VF, Tiwari AK, Gagliano SA, Hosang G, de Luca V, et al. A genome-wide association study of suicide severity scores in bipolar disorder. J Psychiatr Res. 2015;65(Supplement C):23–9. DOI: 10.1016/j.jpsychires.2014.11.002
14. Chang BP, Franklin JC, Ribeiro JD, Fox KR, Bentley KH, Kleiman EM, et al. Biological risk factors for suicidal behaviors: a meta-analysis. Transl Psychiatry. 2016;6:e887. DOI: 10.1038/tp.2016.165
15. Brent DA, Perper JA, Moritz G, Allman C, Friend A, Roth C, et al. Psychiatric risk factors for adolescent suicide: a case-control study. J Am Acad Child Adolesc Psychiatry. 1993;32:521–9. DOI: 10.1097/00004583-199305000-00006
16. Henriksson MM, Aro HM, Marttunen MJ, Heikkinen ME, Isometsä ET, Kuoppasalmi KI, et al. Mental disorders and comorbidity in suicide. Am J Psychiatry. 1993;150:935–40. DOI: 10.1176/ajp.150.6.935
17. Brent DA, Mann JJ. Family genetic studies, suicide, and suicidal behavior. Am J Med Genet C Semin Med Genet. 2005;133C:13–24. DOI: 10.1002/ajmg.c.30042
18. Brent DA, Bridge J, Johnson BA, Connolly J. Suicidal behavior runs in families: a controlled family study of adolescent suicide victims. Arch Gen Psychiatry. 1996;53:1145–52. DOI: 10.1001/archpsyc.1996.01830120085015
19. Barak-Corren Y, Castro VM, Javitt S, Hoffnagle AG, Dai Y, Perlis RH. et al. Predicting suicidal behavior from longitudinal electronic health records. Am J Psychiatry. 2016;174:154–62. DOI: 10.1176/appi.ajp.2016.16010077
20. Walsh CG, Ribeiro JD, Franklin JC. Predicting risk of suicide attempts over time through machine learning. Clin Psychol Sci. 2017;5:216770261769156.
21. McCoy TH, Castro VM, Roberson AM, Snapper LA, Perlis RH. Improving prediction of suicide and accidental death after discharge from general hospitals with natural language processing. JAMA Psychiatry. 2016;73:1064–71. DOI: 10.1001/jamapsychiatry.2016.2172
22. Kessler RC, Stein MB, Petukhova MV, Bliese P, Bossarte RM, Bromet EJ, et al. Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Mol Psychiatry. 2016. http://www.nature.com/doifinder/10.1038/mp.2016.110.
23. Kessler RC, Warner CH, Ivany C, Petukhova MV, Rose S, Bromet EJ. et al. Predicting suicides after psychiatric hospitalization in US Army soldiers: the Army Study to assess risk and resilience in servicemembers (Army STARRS). JAMA Psychiatry. 2014;72:1–9.
24. Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203.
25. Roden D, Pulley J, Basford M, Bernard G, Clayton E, Balser J. et al. Development of a large-scale de-identified DNA biobank to enable personalized medicine. Clin Pharmacol Ther. 2008;84:362–9. DOI: 10.1038/clpt.2008.89
26. Harrell FEJ. Regression modeling strategies. Medicine. 2006;41–51.
27. Smith GCS, Seaman SR, Wood AM, Royston P, White IR. Correcting for optimistic prediction in small data sets. Am J Epidemiol. 2014;180:318–24. DOI: 10.1093/aje/kwu140
28. Bulik-Sullivan BK, Loh P-R, Finucane HK, Ripke S, Yang J, Schizophrenia Working Group of the Psychiatric Genomics Consortium. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47:291–5. DOI: 10.1038/ng.3211
29. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D. et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81:559–75. DOI: 10.1086/519795
30. Zheng J, Erzurumluoglu AM, Elsworth BL, Kemp JP, Howe L, Haycock PC, et al. LD Hub: a centralized database and web interface to perform LD score regression that maximizes the potential of summary level GWAS data for SNP heritability and genetic correlation analysis. Bioinformatics. 2017;33:272–9. DOI: 10.1093/bioinformatics/btw613
31. Okbay A, Baselmans BML, De Neve J-E, Turley P, Nivard MG, Fontana MA, et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet. 2016. http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3552.html.
32. Schizophrenia Working Group of the Psychiatric Genomics Consortium. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7. DOI: 10.1038/nature13595
33. Hammerschlag AR, Stringer S, de Leeuw CA, Sniekers S, Taskesen E, Watanabe K, et al. Genome-wide association analysis of insomnia complaints identifies risk genes and genetic overlap with psychiatric and metabolic traits. Nat Genet. 2017. http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3888.html.
34. Lane JM, Liang J, Vlasac I, Anderson SG, Bechtold DA, Bowden J, et al. Genome-wide association analyses of sleep disturbance traits identify new loci and highlight shared genetics with neuropsychiatric and metabolic traits. Nat Genet. 2017;49:274. DOI: 10.1038/ng.3749
35. A mega-analysis of genome-wide association studies for major depressive disorder. Mol Psychiatry. 2013. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3837431/.
36. Consortium C-DGof the PG. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013;381:1371–9. DOI: 10.1016/S0140-6736(12)62129-1
37. Barban N, Jansen R, Vlaming R, de, Vaez A, Mandemakers JJ, Tropf FC, et al. Genome-wide analysis identifies 12 loci influencing human reproductive behavior. Nat Genet. 2016;48:1462. DOI: 10.1038/ng.3698
38. Okbay A, Beauchamp JP, Fontana MA, Lee JJ, Pers TH, Rietveld CA, et al. Genome-wide association study identifies 74 loci associated with educational attainment. Nature. 2016;533:539–42. DOI: 10.1038/nature17671
39. Pigeon WR, Pinquart M, Conner K. Meta-analysis of sleep disturbance and suicidal thoughts and behaviors. J Clin Psychiatry. 2012;73:1160–7. DOI: 10.4088/JCP.11r07586
40. Ribeiro JD, Pease JL, Gutierrez PM, Silva C, Bernert RA, Rudd MD, et al. Sleep problems outperform depression and hopelessness as cross-sectional and longitudinal predictors of suicidal ideation and behavior in young adults in the military. J Affect Disord. 2012;136:743–50. DOI: 10.1016/j.jad.2011.09.049
41. Ni G, Gratten J, Wray NR, Lee SH. Age at first birth in women is genetically associated with increased risk of schizophrenia. Sci Rep. 2018;8:10168. DOI: 10.1038/s41598-018-28160-z
42. Yang J, Wray NR, Visscher PM. Comparing apples and oranges: equating the power of case-control and quantitative trait association studies. Genet Epidemiol. 2010;34:254–7. DOI: 10.1002/gepi.20497