Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-25T19:49:45.898Z Has data issue: false hasContentIssue false
  • English
  • Français

Genetic correlations between suicide attempts and psychiatric and intermediate phenotypes adjusting for mental disorders

Published online by Cambridge University Press:  10 August 2023

Daisuke Fujikane ,
Kazutaka Ohi Open the ORCID record for Kazutaka Ohi [Opens in a new window] ,
Ayumi Kuramitsu ,
Kentaro Takai ,
Yukimasa Muto ,
Shunsuke Sugiyama  and
Toshiki Shioiri
Daisuke Fujikane
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
Kazutaka Ohi*
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan Department of General Internal Medicine, Kanazawa Medical University, Ishikawa, Japan
Ayumi Kuramitsu
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
Kentaro Takai
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
Yukimasa Muto
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
Shunsuke Sugiyama
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
Toshiki Shioiri
Affiliation:
Department of Psychiatry, Gifu University Graduate School of Medicine, Gifu, Japan
*
Corresponding author: Kazutaka Ohi; Email: k_ohi@gifu-u.ac.jp
Rights & Permissions [Opens in a new window]

Abstract

Background

Suicide attempts are a moderately heritable trait, and genetic correlations with psychiatric and related intermediate phenotypes have been reported. However, as several mental disorders as well as major depressive disorder (MDD) are strongly associated with suicide attempts, these genetic correlations could be mediated by psychiatric disorders. Here, we investigated genetic correlations of suicide attempts with psychiatric and related intermediate phenotypes, with and without adjusting for mental disorders.

Methods

To investigate the genetic correlations, we utilized large-scale genome-wide association study summary statistics for suicide attempts (with and without adjusting for mental disorders), nine psychiatric disorders, and 15 intermediate phenotypes.

Results

Without adjusting for mental disorders, suicide attempts had significant positive genetic correlations with risks of attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, MDD, anxiety disorders and posttraumatic stress disorder; higher risk tolerance; earlier age at first sexual intercourse, at first birth and at menopause; higher parity; lower childhood IQ, educational attainment and cognitive ability; and lower smoking cessation. After adjusting for mental disorders, suicide attempts had significant positive genetic correlations with the risk of MDD; earlier age at first sexual intercourse, at first birth and at menopause; and lower educational attainment. After adjusting for mental disorders, most of the genetic correlations with psychiatric disorders were decreased, while several genetic correlations with intermediate phenotypes were increased.

Conclusions

These findings highlight the importance of considering mental disorders in the analysis of genetic correlations related to suicide attempts and suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts after adjusting for mental disorders.

Keywords

Depressioneducational attainmentgenetic correlationreproductive behaviorssuicide attempts
Type
Original Article
Information
Psychological Medicine , Volume 54 , Issue 3 , February 2024 , pp. 488 - 494
Check for updates
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press

Introduction

Suicide is a major concern for global public health and a leading cause of death globally. According to the World Health Organization (WHO), over 800 000 people die by suicide each year, and many more attempt suicide during their lifetime (WHO, 2019). A suicide attempt refers to a deliberate, self-inflicted act with the intent to end one's life that fails to result in death. Suicide attempts can range from self-harm behaviors to serious, life-threatening actions. The lifetime prevalence of suicide attempts ranges from 3% to 4% in high-income countries (WHO, 2019). Family, twin and adoption studies have shown a familial aggregation of suicidal behaviors (Runeson & Asberg, Reference Runeson and Asberg2003; Tidemalm et al., Reference Tidemalm, Runeson, Waern, Frisell, Carlström, Lichtenstein and Långström2011) and have indicated that genetic factors account for approximately 30–50% of the observed familial aggregation (Fu et al., Reference Fu, Heath, Bucholz, Nelson, Glowinski, Goldberg and Eisen2002; Statham et al., Reference Statham, Heath, Madden, Bucholz, Bierut, Dinwiddie and Martin1998).

To date, several large-scale genome-wide association studies (GWASs) have been conducted to determine the genetic factors that contribute to suicide attempts, suicide death, and suicidal behaviors (Erlangsen et al., Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020; Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022; Ruderfer et al., Reference Ruderfer, Walsh, Aguirre, Tanigawa, Ribeiro, Franklin and Rivas2020; Strawbridge et al., Reference Strawbridge, Ward, Ferguson, Graham, Shaw, Cullen and Smith2019). These studies have identified a few genome-wide significant loci related to the risks of suicide and suicidal behaviors; however, the identified loci varied among studies. Since psychiatric disorders, particularly major depressive disorder (MDD), are strongly linked to suicide (Bachmann, Reference Bachmann2018), several GWASs have investigated genetic associations with and without adjusting for MDD (Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022), determining that the genetic basis for suicide and suicidal behavior is affected by MDD. However, most cases and some controls in these GWASs had various mental disorders, such as attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), schizophrenia (SCZ) and bipolar disorder (BD) as well as MDD (Erlangsen et al., Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020; Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022; Ruderfer et al., Reference Ruderfer, Walsh, Aguirre, Tanigawa, Ribeiro, Franklin and Rivas2020; Strawbridge et al., Reference Strawbridge, Ward, Ferguson, Graham, Shaw, Cullen and Smith2019). We cannot exclude the possibility that these GWAS findings were driven by the mixed and different genetic loadings for psychiatric disorders between suicidal and nonsuicidal participants. Among these GWASs, Erlangsen et al. (Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020) in the Integrative Psychiatric Research (iPSYCH) consortium explored suicide attempts with and without adjusting for MDD as well as other mental disorders in individuals with one or more suicide attempts (n = 6024) and those without any suicide attempts (n = 44 240). These GWASs have indicated that genome-wide significant loci are affected by adjusting for mental disorders, including MDD.

The specific genetic factors that may contribute to the risk of suicide attempts are not fully understood. Understanding the genetic basis of suicide attempts can help inform prevention and intervention efforts. Genetic correlations, i.e. shared genetic factors, refer to the extent to which the same genetic factors contribute to the risk of developing psychiatric disorders and/or the related intermediate phenotypes. It is important to note that genetic correlations do not necessarily imply that one disorder or phenotype causes the other or that the disorders and/or phenotypes are the same. Rather, they suggest that there may be shared genetic risk factors that contribute to the development of psychiatric disorders and/or the related intermediate phenotypes. Several studies have investigated genetic correlations between suicide attempts and psychiatric disorders and the related intermediate phenotypes (Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022; Ruderfer et al., Reference Ruderfer, Walsh, Aguirre, Tanigawa, Ribeiro, Franklin and Rivas2020; Strawbridge et al., Reference Strawbridge, Ward, Ferguson, Graham, Shaw, Cullen and Smith2019). Suicide attempts were genetically correlated with risks of MDD, anxiety disorders, SCZ, BD, ADHD, ASD, posttraumatic stress disorder (PTSD), anorexia nervosa (AN), insomnia, and alcohol use disorder; earlier age at first birth; higher neuroticism; lower educational attainment; and higher smoking initiation (Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022; Ruderfer et al., Reference Ruderfer, Walsh, Aguirre, Tanigawa, Ribeiro, Franklin and Rivas2020; Strawbridge et al., Reference Strawbridge, Ward, Ferguson, Graham, Shaw, Cullen and Smith2019). After adjusting for MDD, the genetic correlations with psychiatric disorders, particularly MDD, anxiety disorders, ASD, PTSD and AN, were reduced (Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022). However, given that a wide range of mental disorders, such as SCZ, BD, ADHD, and PTSD, is associated with increased risk of suicide attempts, genetic factors underlying suicide attempts might be mediated through their impacts on other mental disorders as well as MDD.

The clinical as well as genetic basis between suicide and various psychiatric disorders and related intermediate phenotypes (Bachmann, Reference Bachmann2018; Lewis, Johnson, Cohen, Garcia, & Velez, Reference Lewis, Johnson, Cohen, Garcia and Velez1988; Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mota, Cox, Katz, & Sareen, Reference Mota, Cox, Katz and Sareen2010; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022; Ruderfer et al., Reference Ruderfer, Walsh, Aguirre, Tanigawa, Ribeiro, Franklin and Rivas2020; Strawbridge et al., Reference Strawbridge, Ward, Ferguson, Graham, Shaw, Cullen and Smith2019) motivated us to investigate whether we would find a genetic correlation with suicide even after correcting for various psychiatric disorders in this study. We hypothesized that even after adjusting for mental disorders including SCZ, BD, ASD, AN, or any other mental disorder in addition to MDD, some psychiatric disorders and related intermediate phenotypes would have genetic correlations with suicide attempts. Here, we investigated genetic correlations of suicide attempts (with and without adjusting for mental disorders) (Erlangsen et al., Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020) with nine psychiatric disorders and the 15 related intermediate phenotypes selected based on the clinical and genetic associations using linkage disequilibrium score regression (LDSC) analyses.

Methods

To investigate genetic correlations of suicide attempts (with and without adjusting for mental disorders) with psychiatric and intermediate phenotypes, we extracted GWAS summary statistics for suicide attempts (without and with adjusting for mental disorders; Models 1 and 2, respectively) (Erlangsen et al., Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020), and nine psychiatric disorders and 15 similar but independent intermediate phenotypes selected based on the clinical and genetic associations with suicide attempts (Bachmann, Reference Bachmann2018; Lewis et al., Reference Lewis, Johnson, Cohen, Garcia and Velez1988; Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mota et al., Reference Mota, Cox, Katz and Sareen2010; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022; Ruderfer et al., Reference Ruderfer, Walsh, Aguirre, Tanigawa, Ribeiro, Franklin and Rivas2020; Strawbridge et al., Reference Strawbridge, Ward, Ferguson, Graham, Shaw, Cullen and Smith2019) from individuals with European ancestry (Table 1). The detailed sample information regarding sample collection, genotyping, quality control, and imputation procedures applied in each GWAS has been described previously (Arnold et al., Reference Arnold, Askland, Barlassina, Bellodi, Bienvenu, Black and Zai2018; Barban et al., Reference Barban, Jansen, de Vlaming, Vaez, Mandemakers, Tropf and Mills2016; Benyamin et al., Reference Benyamin, Pourcain, Davis, Davies, Hansell, Brion and Visscher2014; Davies et al., Reference Davies, Lam, Harris, Trampush, Luciano, Hill and Deary2018; Demontis et al., Reference Demontis, Walters, Athanasiadis, Walters, Therrien, Nielsen and Børglum2023; Duncan et al., Reference Duncan, Yilmaz, Gaspar, Walters, Goldstein, Anttila and Bulik2017; Erlangsen et al., Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020; Furberg et al., Reference Furberg, Kim, Dackor, Boerwinkle, Franceschini, Ardissino and Sullivan2010; Grove et al., Reference Grove, Ripke, Als, Mattheisen, Walters, Won and Børglum2019; Karlsson Linnér et al., Reference Karlsson Linnér, Biroli, Kong, Meddens, Wedow, Fontana and Beauchamp2019; Lee et al., Reference Lee, Wedow, Okbay, Kong, Maghzian, Zacher and Cesarini2018; Loh, Kichaev, Gazal, Schoech, & Price, Reference Loh, Kichaev, Gazal, Schoech and Price2018; Luciano et al., Reference Luciano, Hagenaars, Davies, Hill, Clarke, Shirali and Deary2018; Mills et al., Reference Mills, Tropf, Brazel, van Zuydam, Vaez, Pers and Day2021; Mullins et al., Reference Mullins, Forstner, O'Connell, Coombes, Coleman, Qiao and Andreassen2021; Nievergelt et al., Reference Nievergelt, Maihofer, Klengel, Atkinson, Chen, Choi and Koenen2019; Okbay et al., Reference Okbay, Baselmans, De Neve, Turley, Nivard, Fontana and Cesarini2016; Purves et al., Reference Purves, Coleman, Meier, Rayner, Davis, Cheesman and Eley2020; Trubetskoy et al., Reference Trubetskoy, Pardiñas, Qi, Panagiotaropoulou, Awasthi, Bigdeli and O'Donovan2022; van den Berg et al., Reference van den Berg, de Moor, Verweij, Krueger, Luciano, Arias Vasquez and Boomsma2016; Wray et al., Reference Wray, Ripke, Mattheisen, Trzaskowski, Byrne, Abdellaoui and Sullivan2018). Informed consent was obtained from all participants and/or their families in each study cohort. Data availability was approved by each local ethical committee of the relevant institutions.

Table 1. Demographic information for genome-wide association studies (GWASs) of suicide attempts, psychiatric disorders and intermediate phenotypes

Suicide attempts, SA; Mental disorders, MD; PMID, PubMed ID; GWS, genome-wide significant.

a GWS loci were determined by using FUMA (https://fuma.ctglab.nl/). The observed scale heritability h2 for suicide attempts and psychiatric disorders was converted to liability scale heritability using population prevalence and sample prevalence in each study.

Suicide attempts with and without adjusting for mental disorders

GWAS summary statistics regarding suicide attempts with (Model 2) and without (Model 1) adjusting for mental disorders (Erlangsen et al., Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020) are available in the iPSYCH public database (https://ipsych.dk/en/research/downloads).

Case‒control samples were registered through the Danish iPSYCH registration systems. Individuals who were diagnosed with one or more severe mental disorders (ADHD, ASD, SCZ, BD, affective disorders, or AN) according to the 10th revision of the International Classification of Diseases (ICD-10) were included. In addition, a population-based random sample of individuals was also included. Among these subjects, cases (n = 6024) were defined as individuals with one or more recorded incidents of nonfatal suicide attempts. Suicide attempts and a proxy for suicide attempts, such as a mental disorder together with a diagnosis of poisoning by drugs or other substances or injuries to the hand, wrist, or forearm, were identified according to the ICD-10 codes through the Danish iPSYCH registration systems. Controls (n = 44 240) were defined as all persons without one or more suicide attempts. The case‒control group consisted of persons with mental disorders (case, 97.8%; control, 70.0%) and those with no mental disorders (case, 2.2%; control, 30.0%) (Erlangsen et al., Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020). Two different GWAS models (Models 1 and 2) were constructed. Model 1 did not adjust for mental disorders. Model 2 contained binary covariates for the diagnosis of SCZ, BD, affective disorders, ASD, AN, or any other mental disorder.

Intermediate phenotypes

GWAS summary statistics for 15 intermediate phenotypes, including personality traits, reproductive behaviors, cognitive functions, smoking behaviors, extraversion (van den Berg et al., Reference van den Berg, de Moor, Verweij, Krueger, Luciano, Arias Vasquez and Boomsma2016), general risk tolerance (Karlsson Linnér et al., Reference Karlsson Linnér, Biroli, Kong, Meddens, Wedow, Fontana and Beauchamp2019), neuroticism (Luciano et al., Reference Luciano, Hagenaars, Davies, Hill, Clarke, Shirali and Deary2018), subjective well-being (Okbay et al., Reference Okbay, Baselmans, De Neve, Turley, Nivard, Fontana and Cesarini2016), age at menarche (Loh et al., Reference Loh, Kichaev, Gazal, Schoech and Price2018), age at first sexual intercourse (Mills et al., Reference Mills, Tropf, Brazel, van Zuydam, Vaez, Pers and Day2021), age at first birth (Mills et al., Reference Mills, Tropf, Brazel, van Zuydam, Vaez, Pers and Day2021), parity (Barban et al., Reference Barban, Jansen, de Vlaming, Vaez, Mandemakers, Tropf and Mills2016), age at menopause (Loh et al., Reference Loh, Kichaev, Gazal, Schoech and Price2018), childhood IQ (Benyamin et al., Reference Benyamin, Pourcain, Davis, Davies, Hansell, Brion and Visscher2014), educational attainment (Lee et al., Reference Lee, Wedow, Okbay, Kong, Maghzian, Zacher and Cesarini2018), general cognitive ability (Davies et al., Reference Davies, Lam, Harris, Trampush, Luciano, Hill and Deary2018), smoking initiation (Furberg et al., Reference Furberg, Kim, Dackor, Boerwinkle, Franceschini, Ardissino and Sullivan2010), smoking quantity (Furberg et al., Reference Furberg, Kim, Dackor, Boerwinkle, Franceschini, Ardissino and Sullivan2010), and smoking cessation (Furberg et al., Reference Furberg, Kim, Dackor, Boerwinkle, Franceschini, Ardissino and Sullivan2010), were utilized through public databases from the Center for Cognitive Aging and Cognitive Epidemiology at the University of Edinburgh (CCACE) (http://www.ccace.ed.ac.uk/node/335), the iPSYCH (https://ipsych.dk/en/research/downloads), the Genetics of Personality Consortium (GPC) (http://www.tweelingenregister.org/GPC/), the Social Science Genetic Association Consortium (SSGAC) (http://www.thessgac.org/data), the GWAS Catalog (https://www.ebi.ac.uk/gwas/summary-statistics), and the Tobacco and Genetics Consortium. These intermediate phenotypes especially among personality traits, reproductive behaviors, cognitive functions, and smoking behaviors are genetically similar but independent phenotypes (Davies et al., Reference Davies, Lam, Harris, Trampush, Luciano, Hill and Deary2018; Furberg et al., Reference Furberg, Kim, Dackor, Boerwinkle, Franceschini, Ardissino and Sullivan2010; Luciano et al., Reference Luciano, Hagenaars, Davies, Hill, Clarke, Shirali and Deary2018; Mills et al., Reference Mills, Tropf, Brazel, van Zuydam, Vaez, Pers and Day2021; Ohi et al., Reference Ohi, Kuramitsu, Fujikane, Takai, Sugiyama and Shioiri2022a; Ohi, Muto, Takai, Sugiyama, & Shioiri, Reference Ohi, Muto, Takai, Sugiyama and Shioiri2022b).

Linkage disequilibrium score regression analysis

To estimate the genetic correlations of single-nucleotide polymorphisms (SNPs) (rg) between two GWASs, LDSC analyses were performed (Bulik-Sullivan et al., Reference Bulik-Sullivan, Loh, Finucane, Ripke, Yang, Patterson and Neale2015; Ohi et al., Reference Ohi, Shimada, Kataoka, Yasuyama, Kawasaki, Shioiri and Thompson2020b, Reference Ohi, Kuramitsu, Fujikane, Takai, Sugiyama and Shioiri2022a; Ohi, Otowa, Shimada, Sasaki, & Tanii, Reference Ohi, Otowa, Shimada, Sasaki and Tanii2020a). For each GWAS, we filtered the imputed and directly genotyped SNPs in each GWAS to SNPs that overlapped with a HapMap3 SNP panel to restrict the analysis to well-imputed SNPs. Furthermore, insertion‒deletion polymorphisms (indels), structural variants, strand-ambiguous SNPs and SNPs with extremely large effect sizes were removed. Only SNPs with an imputation INFO score >0.90 and minor allele frequency >0.01, if this information was available, were included in the analysis. Regression weights (LD scores, ‘eur_w_ld_chr/’ files, https://github.com/bulik/ldsc) were precomputed using the European-ancestry samples of the 1000 Genomes Project. For each GWAS, LD regression was carried out by regressing the GWAS test statistic (χ2) onto each SNP's LD score. Then, genetic correlations between the two GWASs were calculated. We set a Bonferroni-corrected p value threshold of p < 2.08 × 10−3 (=0.05/24 psychiatric and intermediate phenotypes) to avoid type I error.

Results

Genetic correlations between suicide attempts and psychiatric disorders, with and without adjusting for mental disorders

We first investigated genetic correlations between suicide attempts and psychiatric disorders with and without including mental disorders as covariates (Fig. 1). Suicide attempts were significantly genetically correlated with psychiatric disorders without adjusting for mental disorders; specifically, suicide attempts were genetically correlated with risks of ADHD (rg ± s.e. = 0.61 ± 0.08, p = 3.33 × 10−13), SCZ (0.23 ± 0.06, p = 4.00 × 10−4), BD (0.27 ± 0.06, p = 2.67 × 10−5), MDD (0.69 ± 0.08, p = 3.61 × 10−17), anxiety disorders (0.48 ± 0.10, p = 6.58 × 10−7) and PTSD (0.72 ± 0.18, p = 6.68 × 10−5).

Figure 1. Genetic correlations (rg) between suicide attempts and psychiatric disorders, with and without adjusting for any psychiatric diagnosis. A positive rg indicates that suicide attempts were genetically correlated with the risk of each psychiatric disorder. Error bars represent the standard error. *p < 0.05, **p < 0.01, ***p < 2.08 × 10−3. ADHD, attention-deficit/hyperactivity disorder; ASD, autism spectrum disorder; SCZ, schizophrenia; BD, bipolar disorder; MDD, major depressive disorder; Anxiety, anxiety disorders; PTSD, posttraumatic stress disorder; AN, anorexia nervosa; OCD, obsessive-compulsive disorder.

In contrast, after adjusting for mental disorders, most of the genetic correlations were decreased (Fig. 3, 14.2% decrease, mean rg ± s.e. = −0.05 ± 0.06). After adjusting for mental disorders, suicide attempts were significantly genetically correlated with only the risk of MDD (0.59 ± 0.17, p = 6.00 × 10−4). Risks of ADHD, BD, anxiety disorders and PTSD were not significantly but nominally genetically correlated with suicide attempts after adjusting for mental disorders (p > 2.08 × 10−3 but p < 0.05).

Genetic correlations between suicide attempts and intermediate phenotypes, with and without adjusting for mental disorders

We next investigated genetic correlations between suicide attempts and intermediate phenotypes, including personality traits, reproductive behaviors, cognitive functions, and smoking behaviors, with and without any mental disorders as covariates (Fig. 2). Among several intermediate phenotypes, suicide attempts were significantly genetically correlated with higher risk tolerance (0.33 ± 0.07, p = 1.64 × 10−6), earlier age at first sexual intercourse (−0.64 ± 0.08, p = 3.92 × 10−15), earlier age at first birth (−0.69 ± 0.09, p = 1.74 × 10−14) and earlier age at menopause (−0.41 ± 0.07, p = 1.33 × 10−8), higher parity (0.36 ± 0.10, p = 5.00 × 10−4), lower childhood IQ (−0.58 ± 0.15, p = 1.00 × 10−4), lower educational attainment (−0.41 ± 0.06, p = 8.43 × 10−12), lower cognitive ability (−0.33 ± 0.06, p = 3.10 × 10−8), and lower smoking cessation (−0.60 ± 0.18, p = 7.00 × 10−4), without adjusting for mental disorders. Higher neuroticism, lower subjective well-being, and higher smoking initiation were not significantly but nominally genetically correlated with suicide attempts without adjusting for mental disorders (p > 2.08 × 10−3 but p < 0.05).

Figure 2. Genetic correlations between suicide attempts and intermediate phenotypes, with and without adjusting for any psychiatric diagnosis. Positive and negative rg values indicate that suicide attempts were genetically correlated with high or low intermediate phenotypes, respectively. *p < 0.05, **p < 0.01, ***p < 2.08 × 10−3.

In contrast to the psychiatric disorder results, after adjusting for mental disorders, several genetic correlations with intermediate phenotypes were increased (Fig. 3, 33.5% increase, mean rg ± s.e. = 0.06 ± 0.09). After adjusting for mental disorders, suicide attempts had significant genetic correlations with earlier age at first sexual intercourse (−0.71 ± 0.20, p = 4.00 × 10−4), earlier age at first birth (−0.77 ± 0.23, p = 6.00 × 10−4), earlier age at menopause (−0.52 ± 0.16, p = 1.00 × 10−3) and lower educational attainment (−0.43 ± 0.13, p = 5.00 × 10−4). Higher risk tolerance, lower childhood IQ, lower cognitive ability, and lower smoking cessation had not significantly but nominally genetic correlations with suicide attempts after adjusting for mental disorders (p > 2.08 × 10−3 but p < 0.05).

Figure 3. Genetic correlations (rg) between suicide attempts and psychiatric disorders and intermediate phenotypes were affected by adjusting for mental disorders. MDD, major depressive disorder; EA, educational attainment; menopause, age at menopause; AFS, age at first sexual intercourse; AFB, age at first birth.

Discussion

This is the first study to investigate genetic correlations of suicide attempts with psychiatric disorders and the related intermediate phenotypes, with and without including mental disorders (such as MDD) as covariates. Without adjusting for mental disorders, suicide attempts had significant genetic correlations with risks of ADHD, SCZ, BD, MDD, anxiety disorders and PTSD; higher risk tolerance; earlier age at first sexual intercourse, age at first birth and age at menopause; higher parity; and lower childhood IQ, educational attainment, cognitive ability and smoking cessation. After adjusting for mental disorders, suicide attempts had significant genetic correlations with the risk of MDD, earlier age at first sexual intercourse, earlier age at first birth, earlier age at menopause, and lower educational attainment. These findings highlight the importance of considering mental disorders as covariates in the analysis of genetic correlations between suicide attempts and psychiatric and intermediate phenotypes.

Most participants in GWAS of suicide attempts had mental disorders, in terms of cases with suicide attempts (97.8%) and controls without suicide attempts (70.0%) (Erlangsen et al., Reference Erlangsen, Appadurai, Wang, Turecki, Mors, Werge and Agerbo2020). The mental disorders consisted of MDD (cases, 71.4%; controls, 33.8%) as well as other disorders, such as AN, SCZ, ASD and ADHD. Therefore, differences in the prevalence of mental disorders (except for MDD) between case‒control groups would affect genetic correlations between suicide attempts and psychiatric disorders and the related intermediate phenotypes. Thus, it is important to consider the effects of differences in prevalence rates of mental disorders (except for MDD) on the genetic correlations and to investigate the shared genetic basis of suicide attempts and psychiatric disorders not mediated by various mental disorders.

We found that suicide attempts shared genetic risk factors with susceptibility to MDD (rg = 0.59), even after adjusting for several mental disorders, including MDD. Previous studies have investigated whether genetic correlations between suicide attempts and psychiatric and intermediate phenotypes are mediated by MDD (Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022). Several genetic correlations with psychiatric disorders, such as ADHD, SCZ and BD, were not affected by adjusting for MDD, while other genetic correlations with psychiatric disorders, such as anxiety disorders, PTSD and ASD, were affected by adjusting for MDD (Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022). In this study, we found that most genetic correlations with psychiatric disorders were mediated by mental disorders (Figs 1 and 3). On the other hand, suicide attempts had a genetic correlation with only MDD after adjusting for mental disorders. These findings suggest that even latent MDD susceptibility, which is not currently diagnosed as a mental disorder, may be genetically associated with an increased risk of suicide attempts; thus, early detection of the potential susceptibility to MDD can help prevent suicide.

Genetic correlations between suicide attempts and intermediate phenotypes were much less affected by adjusting for MDD (Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022). Similar to previous studies adjusting for MDD (Li et al., Reference Li, Shabalin, DiBlasi, Gopal, Canuso, Palotie and Coon2023; Mullins et al., Reference Mullins, Kang, Campos, Coleman, Edwards, Galfalvy and Ruderfer2022), in the present study, genetic correlations between suicide attempts and intermediate phenotypes were not decreased but rather increased by adjusting for mental disorders (Figs 2 and 3). As neuroticism and smoking behaviors are genetically and epidemiologically associated with several mental disorders (Liu et al., Reference Liu, Jiang, Wedow, Li, Brazel, Chen and Vrieze2019; Luciano et al., Reference Luciano, Hagenaars, Davies, Hill, Clarke, Shirali and Deary2018), genetic correlations of neuroticism and smoking behaviors with suicide attempts were moderately influenced by adjusting for mental disorders. In contrast, genetic correlations between suicide attempts and reproductive behaviors, such as age at first sexual intercourse (rg = −0.71), age at first birth (rg = −0.77) and age at menopause (rg = −0.52), and lower educational levels (rg = −0.43) were still significant even after adjusting for mental disorders. There is evidence of associations between suicide attempts and reproductive behaviors (Mota et al., Reference Mota, Cox, Katz and Sareen2010). Individuals who have attempted suicide are more likely to engage in risk-taking behaviors, including unprotected sexual behavior, early initiation of sexual activity and unintended pregnancy (Mota et al., Reference Mota, Cox, Katz and Sareen2010). Furthermore, several studies have shown that lower educational attainment is associated with a higher risk of suicide attempts (Lewis et al., Reference Lewis, Johnson, Cohen, Garcia and Velez1988). Although these relationships of suicide attempts with reproductive behaviors and educational attainment might be due to a variety of factors, including increased financial stress, lower social support, and potential risks of mental disorders, our findings suggest that these associations could be partially derived from shared genetic factors.

There are some limitations to the interpretations of our findings. Sample sizes were inconsistent among GWASs for psychiatric disorders and intermediate phenotypes. As the statistical power of the LDSC analysis roughly varies with n2, even moderate correlations might not be significantly detectable in smaller samples, such as correlations with smoking cessation (Table 1 and Fig. 2, rg > 0.60). Therefore, careful interpretation is needed when comparing genetic correlations among GWASs with different sample sizes. The s.e. of the genetic correlations (rg) might serve as a reference for comparisons among GWASs with different sample sizes. If the power of further GWASs of suicide attempts is increased, a Mendelian randomization study could investigate potential causal relationships between these risk phenotypes, such as reproductive behaviors and suicide attempts.

In conclusion, we investigated whether genetic correlations of suicide attempts with psychiatric and intermediate phenotypes were mediated by mental disorders. After adjusting for mental disorders, the strength of genetic correlations between suicide attempts and psychiatric disorders were reduced, while those between suicide attempts and intermediate phenotypes were increased. Our findings suggest that susceptibility to MDD, reproductive behaviors, and lower educational levels share a genetic basis with suicide attempts even after adjusting for mental disorders.

Acknowledgements

This work was supported by Grants-in-Aid for Scientific Research (C) (19K08081, 21K07497, 22K07614) from the Japan Society for the Promotion of Science (JSPS), AMED under grant number JP21uk1024002, AMED under grant number JP22dk0307112, and a grant from the Smoking Research Foundation. We would like to thank all individuals who participated in this study.

Competing interest

None.

References

Arnold, P. D., Askland, K. D., Barlassina, C., Bellodi, L., Bienvenu, O. J., Black, D., … Zai, G. (2018). Revealing the complex genetic architecture of obsessive-compulsive disorder using meta-analysis. Molecular Psychiatry, 23(5), 1181–1188. doi: 10.1038/mp.2017.154Google Scholar
Bachmann, S. (2018). Epidemiology of suicide and the psychiatric perspective. International Journal of Environmental Research and Public Health, 15(7), 1425. doi: 10.3390/ijerph15071425.Google Scholar
Barban, N., Jansen, R., de Vlaming, R., Vaez, A., Mandemakers, J. J., Tropf, F. C., … Mills, M. C. (2016). Genome-wide analysis identifies 12 loci influencing human reproductive behavior. Nature Genetics, 48(12), 1462–1472. doi: 10.1038/ng.3698Google Scholar
Benyamin, B., Pourcain, B., Davis, O. S., Davies, G., Hansell, N. K., Brion, M. J., … Visscher, P. M. (2014). Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Molecular Psychiatry, 19(2), 253–258. doi: 10.1038/mp.2012.184Google Scholar
Bulik-Sullivan, B. K., Loh, P. R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., … Neale, B. M. (2015). LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nature Genetics, 47(3), 291–295. doi: 10.1038/ng.3211Google Scholar
Davies, G., Lam, M., Harris, S. E., Trampush, J. W., Luciano, M., Hill, W. D., … Deary, I. J. (2018). Study of 300486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nature Communications, 9(1), 2098. doi: 10.1038/s41467-018-04362-xGoogle Scholar
Demontis, D., Walters, G. B., Athanasiadis, G., Walters, R., Therrien, K., Nielsen, T. T., … Børglum, A. D. (2023). Genome-wide analyses of ADHD identify 27 risk loci, refine the genetic architecture and implicate several cognitive domains. Nature Genetics, 55(2), 198–208. doi: 10.1038/s41588-022-01285-8Google Scholar
Duncan, L., Yilmaz, Z., Gaspar, H., Walters, R., Goldstein, J., Anttila, V., … Bulik, C. M. (2017). Significant locus and metabolic genetic correlations revealed in genome-wide association study of anorexia nervosa. American Journal of Psychiatry, 174(9), 850–858. doi: 10.1176/appi.ajp.2017.16121402Google Scholar
Erlangsen, A., Appadurai, V., Wang, Y., Turecki, G., Mors, O., Werge, T., … Agerbo, E. (2020). Genetics of suicide attempts in individuals with and without mental disorders: A population-based genome-wide association study. Molecular Psychiatry, 25(10), 2410–2421. doi: 10.1038/s41380-018-0218-yGoogle Scholar
Fu, Q., Heath, A. C., Bucholz, K. K., Nelson, E. C., Glowinski, A. L., Goldberg, J., … Eisen, S. A. (2002). A twin study of genetic and environmental influences on suicidality in men. Psychological Medicine, 32(1), 11–24. doi: 10.1017/s0033291701004846Google Scholar
Furberg, H., Kim, Y., Dackor, J., Boerwinkle, E., Franceschini, N., Ardissino, D., … Sullivan, P. F. (2010). Genome-wide meta-analyses identify multiple loci associated with smoking behavior. Nature Genetics, 42(5), 441–447. doi: 10.1038/ng.571Google Scholar
Grove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R. K., Won, H., … Børglum, A. D. (2019). Identification of common genetic risk variants for autism spectrum disorder. Nature Genetics, 51(3), 431–444. doi: 10.1038/s41588-019-0344-8CrossRefGoogle ScholarPubMed
Karlsson Linnér, R., Biroli, P., Kong, E., Meddens, S. F. W., Wedow, R., Fontana, M. A., … Beauchamp, J. P. (2019). Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nature Genetics, 51(2), 245–257. doi: 10.1038/s41588-018-0309-3Google Scholar
Lee, J. J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., … Cesarini, D. (2018). Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nature Genetics, 50(8), 1112–1121. doi: 10.1038/s41588-018-0147-3Google Scholar
Lewis, S. A., Johnson, J., Cohen, P., Garcia, M., & Velez, C. N. (1988). Attempted suicide in youth: Its relationship to school achievement, educational goals, and socioeconomic status. Journal of Abnormal Child Psychology, 16(4), 459–471. doi: 10.1007/bf00914175Google Scholar
Li, Q. S., Shabalin, A. A., DiBlasi, E., Gopal, S., Canuso, C. M., Palotie, A., … Coon, H. (2023). Genome-wide association study meta-analysis of suicide death and suicidal behavior. Molecular Psychiatry, 28(2), 891–900. doi: 10.1038/s41380-022-01828-9.Google Scholar
Liu, M., Jiang, Y., Wedow, R., Li, Y., Brazel, D. M., Chen, F., … Vrieze, S. (2019). Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nature Genetics, 51(2), 237–244. doi: 10.1038/s41588-018-0307-5Google Scholar
Loh, P. R., Kichaev, G., Gazal, S., Schoech, A. P., & Price, A. L. (2018). Mixed-model association for biobank-scale datasets. Nature Genetics, 50(7), 906–908. doi: 10.1038/s41588-018-0144-6Google Scholar
Luciano, M., Hagenaars, S. P., Davies, G., Hill, W. D., Clarke, T. K., Shirali, M., … Deary, I. J. (2018). Association analysis in over 329,000 individuals identifies 116 independent variants influencing neuroticism. Nature Genetics, 50(1), 6–11. doi: 10.1038/s41588-017-0013-8Google Scholar
Mills, M. C., Tropf, F. C., Brazel, D. M., van Zuydam, N., Vaez, A., Pers, T. H., … Day, F. R. (2021). Identification of 371 genetic variants for age at first sex and birth linked to externalising behaviour. Nature Human Behaviour, 5(12), 1717–1730. doi: 10.1038/s41562-021-01135-3Google Scholar
Mota, N. P., Cox, B. J., Katz, L. Y., & Sareen, J. (2010). Relationship between mental disorders/suicidality and three sexual behaviors: Results from the national comorbidity survey replication. Archives of Sexual Behavior, 39(3), 724–734. doi: 10.1007/s10508-008-9463-5Google Scholar
Mullins, N., Forstner, A. J., O'Connell, K. S., Coombes, B., Coleman, J. R. I., Qiao, Z., … Andreassen, O. A. (2021). Genome-wide association study of more than 40000 bipolar disorder cases provides new insights into the underlying biology. Nature Genetics, 53(6), 817–829. doi: 10.1038/s41588-021-00857-4Google Scholar
Mullins, N., Kang, J., Campos, A. I., Coleman, J. R. I., Edwards, A. C., Galfalvy, H., … Ruderfer, D. M. (2022). Dissecting the shared genetic architecture of suicide attempt, psychiatric disorders, and known risk factors. Biological Psychiatry, 91(3), 313–327. doi: 10.1016/j.biopsych.2021.05.029Google Scholar
Nievergelt, C. M., Maihofer, A. X., Klengel, T., Atkinson, E. G., Chen, C. Y., Choi, K. W., … Koenen, K. C. (2019). International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci. Nature Communications, 10(1), 4558. doi: 10.1038/s41467-019-12576-wGoogle Scholar
Ohi, K., Kuramitsu, A., Fujikane, D., Takai, K., Sugiyama, S., & Shioiri, T. (2022a). Shared genetic basis between reproductive behaviors and anxiety-related disorders. Molecular Psychiatry, 27(10), 4103–4112. doi: 10.1038/s41380-022-01667-8Google Scholar
Ohi, K., Muto, Y., Takai, K., Sugiyama, S., & Shioiri, T. (2022b). Investigating genetic overlaps of the genetic factor differentiating schizophrenia from bipolar disorder with cognitive function and hippocampal volume. BJPsych Open, 8(1), e33. doi: 10.1192/bjo.2021.1086Google Scholar
Ohi, K., Otowa, T., Shimada, M., Sasaki, T., & Tanii, H. (2020a). Shared genetic etiology between anxiety disorders and psychiatric and related intermediate phenotypes. Psychological Medicine, 50(4), 692–704. doi: 10.1017/s003329171900059xGoogle Scholar
Ohi, K., Shimada, T., Kataoka, Y., Yasuyama, T., Kawasaki, Y., Shioiri, T., & Thompson, P. M. (2020b). Genetic correlations between subcortical brain volumes and psychiatric disorders. British Journal of Psychiatry, 216(5), 280–283. doi: 10.1192/bjp.2019.277Google Scholar
Okbay, A., Baselmans, B. M., De Neve, J. E., Turley, P., Nivard, M. G., Fontana, M. A., … Cesarini, D. (2016). Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nature Genetics, 48(6), 624–633. doi: 10.1038/ng.3552Google Scholar
Purves, K. L., Coleman, J. R. I., Meier, S. M., Rayner, C., Davis, K. A. S., Cheesman, R., … Eley, T. C. (2020). A major role for common genetic variation in anxiety disorders. Molecular Psychiatry, 25(12), 3292–3303. doi: 10.1038/s41380-019-0559-1Google Scholar
Ruderfer, D. M., Walsh, C. G., Aguirre, M. W., Tanigawa, Y., Ribeiro, J. D., Franklin, J. C., & Rivas, M. A. (2020). Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide. Molecular Psychiatry, 25(10), 2422–2430. doi: 10.1038/s41380-018-0326-8Google Scholar
Runeson, B., & Asberg, M. (2003). Family history of suicide among suicide victims. American Journal of Psychiatry, 160(8), 1525–1526. doi: 10.1176/appi.ajp.160.8.1525Google Scholar
Statham, D. J., Heath, A. C., Madden, P. A., Bucholz, K. K., Bierut, L., Dinwiddie, S. H., … Martin, N. G. (1998). Suicidal behaviour: An epidemiological and genetic study. Psychological Medicine, 28(4), 839–855. doi: 10.1017/s0033291798006916Google Scholar
Strawbridge, R. J., Ward, J., Ferguson, A., Graham, N., Shaw, R. J., Cullen, B., … Smith, D. J. (2019). Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide. EBioMedicine, 41, 517–525. doi: 10.1016/j.ebiom.2019.02.005Google Scholar
Tidemalm, D., Runeson, B., Waern, M., Frisell, T., Carlström, E., Lichtenstein, P., & Långström, N. (2011). Familial clustering of suicide risk: A total population study of 11.4 million individuals. Psychological Medicine, 41(12), 2527–2534. doi: 10.1017/s0033291711000833Google Scholar
Trubetskoy, V., Pardiñas, A. F., Qi, T., Panagiotaropoulou, G., Awasthi, S., Bigdeli, T. B., … O'Donovan, M. C. (2022). Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature, 604(7906), 502–508. doi: 10.1038/s41586-022-04434-5Google Scholar
van den Berg, S. M., de Moor, M. H., Verweij, K. J., Krueger, R. F., Luciano, M., Arias Vasquez, A., … Boomsma, D. I. (2016). Meta-analysis of genome-wide association studies for extraversion: Findings from the genetics of personality consortium. Behavior Genetics, 46(2), 170–182. doi: 10.1007/s10519-015-9735-5Google Scholar
WHO. (2019). Summary tables of mortality estimates by cause, age and sex, globally and by region, 2000–2016. https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/ghe-leading-causes-of-deathGoogle Scholar
Wray, N. R., Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., … Sullivan, P. F. (2018). Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nature Genetics, 50(5), 668–681. doi: 10.1038/s41588-018-0090-3Google Scholar
Figure 0

Table 1. Demographic information for genome-wide association studies (GWASs) of suicide attempts, psychiatric disorders and intermediate phenotypes

Figure 1

Figure 1. Genetic correlations (rg) between suicide attempts and psychiatric disorders, with and without adjusting for any psychiatric diagnosis. A positive rg indicates that suicide attempts were genetically correlated with the risk of each psychiatric disorder. Error bars represent the standard error. *p < 0.05, **p < 0.01, ***p < 2.08 × 10−3. ADHD, attention-deficit/hyperactivity disorder; ASD, autism spectrum disorder; SCZ, schizophrenia; BD, bipolar disorder; MDD, major depressive disorder; Anxiety, anxiety disorders; PTSD, posttraumatic stress disorder; AN, anorexia nervosa; OCD, obsessive-compulsive disorder.

Figure 2

Figure 2. Genetic correlations between suicide attempts and intermediate phenotypes, with and without adjusting for any psychiatric diagnosis. Positive and negative rg values indicate that suicide attempts were genetically correlated with high or low intermediate phenotypes, respectively. *p < 0.05, **p < 0.01, ***p < 2.08 × 10−3.

Figure 3

Figure 3. Genetic correlations (rg) between suicide attempts and psychiatric disorders and intermediate phenotypes were affected by adjusting for mental disorders. MDD, major depressive disorder; EA, educational attainment; menopause, age at menopause; AFS, age at first sexual intercourse; AFB, age at first birth.