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Suicidal behavior and substance use disorders (SUDs) are important public health concerns. Prior suicide attempts and SUDs are two of the most consistent predictors of suicide death, and clarifying the role of SUDs in the transition from suicide attempt to suicide death could inform prevention efforts.
We used national Swedish registry data to identify individuals born 1960–1985, with an index suicide attempt in 1997–2017 (N = 74 873; 46.7% female). We assessed risk of suicide death as a function of registration for a range of individual SUDs. We further examined whether the impact of SUDs varied as a function of (i) aggregate genetic liability to suicidal behavior, or (ii) age at index suicide attempt.
In univariate models, risk of suicide death was higher among individuals with any SUD registration [hazard ratios (HRs) = 2.68–3.86]. In multivariate models, effects of specific SUDs were attenuated, but remained elevated for AUD (HR = 1.86 95% confidence intervals 1.68–2.05), opiates [HR = 1.58 (1.37–1.82)], sedatives [HR = 1.93 (1.70–2.18)], and multiple substances [HR = 2.09 (1.86–2.35)]. In secondary analyses, the effects of most, but not all, SUD were exacerbated by higher levels of genetic liability to suicide death, and among individuals who were younger at their index suicide attempt.
In the presence of a strong predictor of suicide death – a prior attempt – substantial predictive power is still attributable to SUDs. Individuals with SUDs may warrant additional suicide screening and prevention efforts, particularly in the context of a family history of suicidal behavior or early onset of suicide attempt.
Genetic factors contribute to the intergenerational transmission of alcohol misuse, but not all individuals at high genetic risk develop problems. The present study examined adolescent relationships with parents, peers, and romantic partners as predictors of realized resistance, defined as high biological risk for disorder combined with a healthy outcome, to alcohol initiation, heavy episodic drinking, and alcohol use disorder (AUD). Data were from the Collaborative Study on the Genetics of Alcoholism (N = 1,858; 49.9% female; mean age at baseline = 13.91 years). Genetic risk, indexed using family history density and polygenic risk scores for alcohol problems and AUD, was used to define alcohol resistance. Adolescent predictors included parent-child relationship quality, parental monitoring, peer drinking, romantic partner drinking, and social competence. There was little support for the hypothesis that social relationship factors would promote alcohol resistance, with the exception that higher father-child relationship quality was associated with higher resistance to alcohol initiation (
$$\hat \beta $$
= −0.19, 95% CI = −0.35, −0.03). Unexpectedly, social competence was associated with lower resistance to heavy episodic drinking (
$$\hat \beta $$
= 0.10, 95% CI = 0.01, 0.20). This pattern of largely null effects underscores how little is known about resistance processes among those at high genetic risk for AUD.
Previous studies have demonstrated substantial associations between substance use disorders (SUD) and suicidal behavior. The current study empirically assesses the extent to which shared genetic and/or environmental factors contribute to associations between alcohol use disorders (AUD) or drug use disorders (DUD) and suicidal behavior, including attempts and death.
The authors used Swedish national registry data, including medical, pharmacy, criminal, and death registrations, for a large cohort of twins, full siblings, and half siblings (N = 1 314 990) born 1960–1980 and followed through 2017. They conducted twin-sibling modeling of suicide attempt (SA) or suicide death (SD) with AUD and DUD to estimate genetic and environmental correlations between outcomes. Analyses were stratified by sex.
Genetic correlations between SA and SUD ranged from rA = 0.60–0.88; corresponding shared environmental correlations were rC = 0.42–0.89 but accounted for little overall variance; and unique environmental correlations were rE = 0.42–0.57. When replacing attempt with SD, genetic and shared environmental correlations with AUD and DUD were comparable (rA = 0.48–0.72, rC = 0.92–1.00), but were attenuated for unique environmental factors (rE = −0.01 to 0.31).
These findings indicate that shared genetic and unique environmental factors contribute to comorbidity of suicidal behavior and SUD, in conjunction with previously reported causal associations. Thus, each outcome should be considered an indicator of risk for the others. Opportunities for joint prevention and intervention, while limited by the polygenic nature of these outcomes, may be feasible considering moderate environmental correlations between SA and SUD.
How does genetic liability to suicide attempt (SA), suicide death (SD), major depression (MD), bipolar disorder (BD), schizophrenia (SZ), alcohol use disorder (AUD), and drug use disorder (DUD) impact on risk for SA and SD?
In the Swedish general population born 1932–1995 and followed through 2017 (n = 7 661 519), we calculate family genetic risk scores (FGRS) for SA, SD, MD, BD, SZ, AUD, and DUD. Registration for SA and SD was assessed from Swedish national registers.
In univariate and multivariate models predicting SA, FGRS were highest for SA, AUD, DUD, and MD. In univariate models predicting SD, the strongest FGRS were AUD, DUD, SA, and SD. In multivariate models, the FGRS for SA and AUD were higher in predicting SA while the FGRS for SD, BD, and SZ were higher in predicting SD. Higher FGRS for all disorders significantly predicted both younger age at first SA and frequency of attempts. For SD, higher FGRS for MD, AUD, and SD predicted later age at SD. Mediation of FGRS effects on SA and SD was more pronounced for SD than SA, strongest for AUD, DUD, and SZ FGRS and weakest for MD.
FGRS for both SA and SD and for our five psychiatric disorders impact on risk for SA and SD in a complex manner. While some of the impact of genetic risk factors for psychiatric disorders on risk for SA and SD is mediated through developing the disorders, these risks also predispose directly to suicidal behaviors.
Oral contraceptive use has been previously associated with an increased risk of suicidal behavior in some, but not all, samples. The use of large, representative, longitudinally-assessed samples may clarify the nature of this potential association.
We used Swedish national registries to identify women born between 1991 and 1995 (N = 216 702) and determine whether they retrieved prescriptions for oral contraceptives. We used Cox proportional hazards models to test the association between contraceptive use and first observed suicidal event (suicide attempt or death) from age 15 until the end of follow-up in 2014 (maximum age 22.4). We adjusted for covariates, including mental illness and parental history of suicide.
In a crude model, use of combination or progestin-only oral contraceptives was positively associated with suicidal behavior, with hazard ratios (HRs) of 1.73–2.78 after 1 month of use, and 1.25–1.82 after 1 year of use. Accounting for sociodemographic, parental, and psychiatric variables attenuated these associations, and risks declined with increasing duration of use: adjusted HRs ranged from 1.56 to 2.13 1 month beyond the initiation of use, and from 1.19 to 1.48 1 year after initiation of use. HRs were higher among women who ceased use during the observation period.
Young women using oral contraceptives may be at increased risk of suicidal behavior, but risk declines with increased duration of use. Analysis of former users suggests that women susceptible to depression/anxiety are more likely to cease hormonal contraceptive use. Additional studies are necessary to determine whether the observed association is attributable to a causal mechanism.
Alcohol use disorder (AUD) is common and associated with increased risk of suicide.
To examine healthcare utilisation prior to suicide in persons with AUD in a large population-based cohort, which may reveal opportunities for prevention.
A national cohort study was conducted of 6 947 191 adults in Sweden in 2002, including 256 647 (3.7%) with AUD, with follow-up for suicide through 2015. A nested case–control design examined healthcare utilisation among people with AUD who died by suicide and 10:1 age- and gender-matched controls.
In 86.7 million person-years of follow-up, 15 662 (0.2%) persons died by suicide, including 2601 (1.0%) with AUD. Unadjusted and adjusted relative risks for suicide associated with AUD were 8.15 (95% CI 7.86–8.46) and 2.22 (95% CI 2.11–2.34). Of the people with AUD who died by suicide, 39.7% and 75.6% had a healthcare encounter <2 weeks or <3 months before the index date respectively, compared with 6.3% and 25.4% of controls (adjusted prevalence ratio (PR) and difference (PD), <2 weeks: PR = 3.86, 95% CI 3.50–4.25, PD = 26.4, 95% CI 24.2–28.6; <3 months: PR = 2.03, 95% CI 1.94–2.12, PD = 34.9, 95% CI 32.6–37.1). AUD accounted for more healthcare encounters within 2 weeks of suicide among men than women (P = 0.01). Of last encounters, 48.1% were in primary care and 28.9% were in specialty out-patient clinics, mostly for non-psychiatric diagnoses.
Suicide among persons with AUD is often shortly preceded by healthcare encounters in primary care or specialty out-patient clinics. Encounters in these settings are important opportunities to identify active suicidality and intervene accordingly in patients with AUD.
Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.
We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.
In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47–0.68%, p = 2.0 × 10−8–1.0 × 10−10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10−8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10−6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10−11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10−7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10−16).
AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.
Can drug abuse (DA) be transmitted psychologically between adult siblings consistent with a social contagion model?
We followed Swedish sibling pairs born in 1932–1990 until one of them, sibling1 (S1), had a first DA registration. We then examined, using Cox regression, the hazard rate for a first registration for DA in sibling2 (S2) within 3 years of a first DA registration in S1 as a function of their geographical proximity. We examined 153 294 informative pairs. To control for familial confounding, we repeated these analyses in sibships containing multiple pairs, comparing risk in different siblings with their proximity to S1. DA was recorded in medical, criminal or pharmacy registries.
The best-fit model predicted risk for DA in S2 as a function of the log of kilometres between S1 and S2 with parameter estimates (±95% confidence intervals) of 0.94 (0.92; 0.95). Prediction of DA included effects of cohabitation and an interaction of proximity and time since S1 registration with stronger effects of proximity early in the follow-up period. Proximity effects were stronger for smaller S1–S2 age differences and for same- v. opposite-sex pairs. Sibship analyses confirmed sibling-pair results.
Consistent with a social contagion model, the probability of transmission of a first registration for DA in sibling pairs is related to their geographical proximity and similarity in age and sex. Such effects for DA are time-dependent and include cohabitation effects. These results illustrate the complexity of the familial aggregation of DA and support efforts to reduce their contagious spread within families in adulthood.
The Psychiatric Genomics Consortium (PGC) has made major advances in the molecular etiology of MDD, confirming that MDD is highly polygenic. Pathway enrichment results from PGC meta-analyses can also be used to help inform molecular drug targets. Prior to any knowledge of molecular biomarkers for MDD, drugs targeting molecular pathways (MPs) proved successful in treating MDD. It is possible that examining polygenicity within specific MPs implicated in MDD can further refine molecular drug targets.
Using a large case–control GWAS based on low-coverage whole genome sequencing (N = 10 640) in Han Chinese women, we derived polygenic risk scores (PRS) for MDD and for MDD specific to each of over 300 MPs previously shown to be relevant to psychiatric diagnoses. We then identified sets of PRSs, accounting for critical covariates, significantly predictive of case status.
Over and above global MDD polygenic risk, polygenic risk within the GO: 0017144 drug metabolism pathway significantly predicted recurrent depression after multiple testing correction. Secondary transcriptomic analysis suggests that among genes in this pathway, CYP2C19 (family of Cytochrome P450) and CBR1 (Carbonyl Reductase 1) might be most relevant to MDD. Within the cases, pathway-based risk was additionally associated with age at onset of MDD.
Results indicate that pathway-based risk might inform etiology of recurrent major depression. Future research should examine whether polygenicity of the drug metabolism gene pathway has any association with clinical presentation or treatment response. We discuss limitations to the generalizability of these preliminary findings, and urge replication in future research.
Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.
Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).
Positive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation.
This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.
Identifying genetic relationships between complex traits in emerging adulthood can provide useful etiological insights into risk for psychopathology. College-age individuals are under-represented in genomic analyses thus far, and the majority of work has focused on the clinical disorder or cognitive abilities rather than normal-range behavioral outcomes.
This study examined a sample of emerging adults 18–22 years of age (N = 5947) to construct an atlas of polygenic risk for 33 traits predicting relevant phenotypic outcomes. Twenty-eight hypotheses were tested based on the previous literature on samples of European ancestry, and the availability of rich assessment data allowed for polygenic predictions across 55 psychological and medical phenotypes.
Polygenic risk for schizophrenia (SZ) in emerging adults predicted anxiety, depression, nicotine use, trauma, and family history of psychological disorders. Polygenic risk for neuroticism predicted anxiety, depression, phobia, panic, neuroticism, and was correlated with polygenic risk for cardiovascular disease.
These results demonstrate the extensive impact of genetic risk for SZ, neuroticism, and major depression on a range of health outcomes in early adulthood. Minimal cross-ancestry replication of these phenomic patterns of polygenic influence underscores the need for more genome-wide association studies of non-European populations.
The relationship between the genetic and environmental risk factors for alcohol use disorders (AUD) detected in Swedish medical, pharmacy, and criminal registries has not been hitherto examined. Prior twin studies have varied with regard to the detection of shared environmental effects and sex differences in the etiology of AUD. In this report, structural equation modeling in OpenMx was applied to (1) the three types of alcohol registration in a population-based sample of male–male twins and reared-together full and half siblings (total 208,810 pairs), and (2) AUD, as a single diagnosis, in male–male, female–female, and opposite-sex (OS) twins and reared-together full and half siblings (total 787,916 pairs). An independent pathway model fit best to the three forms of registration and indicated that between 70% and 92% of the genetic and 63% and 98% of the shared environmental effects were shared in common with the remainder unique to each form of AUD registration. Criminal registration had the largest proportion of unique genetic and environmental factors. The best fit model for AUD estimated the heritability to be 22% and 57%, respectively, in females and males. Both shared (12% vs. 6%) and special twin environment (29% vs. 2%) were substantially more important in females versus males. In conclusion, AUD ascertained from medical, pharmacy, and criminal Swedish registries largely share the same genetic and environmental risk factors. Large sex differences in the etiology of AUD were seen in this sample, with substantially stronger familial environmental and weaker genetic effects in females versus males.
Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use.