Are genetic risk factors for current depressive symptoms good proxies for genetic risk factors for syndromal major depression (MD)?

In over 9000 twins from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders, the occurrence of all nine DSM symptomatic criteria for MD in the last year was assessed at personal interview and then grouped by their temporal co-occurrence. The DSM criteria which occurred outside (OUT) v. inside of (IN) MD episodes were then separated. We calculated tetrachoric correlations for OUT and IN depressive criteria in monozygotic (MZ) and dizygotic (DZ) pairs and fitted univariate and bivariate ACE twin models using OpenMx.

The mean twin correlations (±95% CIs) for IN depressive criteria were substantially higher than for OUT depressive criteria in both MZ [+0.35 (0.32–0.38) v. 0.20 (0.17–0.24)] and DZ pairs [0.20 (0.17–0.24) v. 0.10 (0.04–0.16]. The mean IN–OUT cross-correlation in MZ and DZ pairs was modest [+0.15 (0.07–0.24) and +0.07 (0.03–0.12)]. The mean heritability estimates for the nine In v. Out depressive criteria was 0.31 (0.22–0.41) and 0.15 (0.08–0.21), in MZ and DZ pairs, respectively. The mean genetic correlation between the nine IN and OUT depressive criteria was +0.07 (−0.07 to 0.21).

Depressive criteria occurring outside depressive episodes are less heritable than those occurring within. These two ways criteria can manifest are not closely genetically related. Current depressive symptoms – most of which are occurring outside of depressive episodes – are not, for genetic studies, good proxies for MD.

To determine, in a general population, how much rates of stress reactions (SR), major depression (MD), alcohol-use disorder (AUD) and drug-use disorder (DUD) increase after the death of close relatives.

SR, MD, AUD, and DUD registrations were assessed from national Swedish registries. From the population followed from 2000 to 2018, those exposed to death of a close relative in 2002–2016 were matched to unexposed controls and analyzed in males and females by a controlled pre-post design using a difference-in-difference method.

Substantial, brief increases in risk for SR and more modest prolonged increases in MD were observed after death of relatives in both men and women greatest with children, followed by spouses, parents, and siblings. Relatively long-lasting modest increases in AUD but not DUD were also observed following death of relatives. The absolute increases for SR and MD were greater in females than males and for AUD greater in males than females. However, logistic regression analyses showed most effects did not differ significantly by sex. Consistently larger increases in disorder risk were seen with the death of younger v. older parents, siblings, and spouses and with accidental v. non-accidental death in children.

Applying a matched cohort design to Swedish population registries, death of close relatives was associated with, and likely caused, substantial increases in rates of SR, MD, and AUD, consistent with smaller prior clinical investigations. Through such registries, we can, in large representative samples, integrate the impact of exposures to selected environmental adversities into disorder risk pathways.

To clarify, in a national sample, associations between risk for seven psychiatric and substance use disorders and five key transitions in Sweden's public educational system.

Swedish-born individuals (1972–1995, N = 1 997 910) were followed through 12-31-2018, at mean age 34.9. We predicted, from these educational transitions, risk for major depression (MD), obsessive-compulsive disorder (OCD), bipolar disorder (BD), schizophrenia (SZ), anorexia nervosa (AN), alcohol use disorder (AUD), and drug use disorder (DUD), assessed from Swedish national registers, by Cox regression, censoring individuals with onsets ⩽17. We also predicted risk from the deviation of grades from family-genetic expectations (deviation 1) and from changes in grades from ages 16 to 19 (deviation 2).

We observed four major risk patterns across transitions in our disorders: (i) MD and BD, (ii) OCD and SZ, (iii) AUD and DUD, and (iv) AN. Failing early educational transitions had the greatest impact on risk for OCD and SZ while for other disorders, not progressing from basic to upper high school had the largest effect. Completing vocational v. college-prep upper high school was strongly associated with risk for AUD and DUD, had little relation with MD, OCD, BD, and SZ risk, and was protective for AN. Deviation 1 predicted risk most strongly for SZ, AN, and MD. Deviation 2 predicted risk most strongly for SZ, AUD, and DUD.

The pattern of educational transitions and within family and within person development deviations are strongly and relatively specifically associated with future risk for seven psychiatric and substance-use disorders.

Psychotic disorders and schizotypal traits aggregate in the relatives of probands with schizophrenia. It is currently unclear how variability in symptom dimensions in schizophrenia probands and their relatives is associated with polygenic liability to psychiatric disorders.

To investigate whether polygenic risk scores (PRSs) can predict symptom dimensions in members of multiplex families with schizophrenia.

The largest genome-wide data-sets for schizophrenia, bipolar disorder and major depressive disorder were used to construct PRSs in 861 participants from the Irish Study of High-Density Multiplex Schizophrenia Families. Symptom dimensions were derived using the Operational Criteria Checklist for Psychotic Disorders in participants with a history of a psychotic episode, and the Structured Interview for Schizotypy in participants without a history of a psychotic episode. Mixed-effects linear regression models were used to assess the relationship between PRS and symptom dimensions across the psychosis spectrum.

Schizophrenia PRS is significantly associated with the negative/disorganised symptom dimension in participants with a history of a psychotic episode (P = 2.31 × 10−4) and negative dimension in participants without a history of a psychotic episode (P = 1.42 × 10−3). Bipolar disorder PRS is significantly associated with the manic symptom dimension in participants with a history of a psychotic episode (P = 3.70 × 10−4). No association with major depressive disorder PRS was observed.

Polygenic liability to schizophrenia is associated with higher negative/disorganised symptoms in participants with a history of a psychotic episode and negative symptoms in participants without a history of a psychotic episode in multiplex families with schizophrenia. These results provide genetic evidence in support of the spectrum model of schizophrenia, and support the view that negative and disorganised symptoms may have greater genetic basis than positive symptoms, making them better indices of familial liability to schizophrenia.

We need to better understand the frequency and predictors of opioid use disorder (OUD) after first opioid prescription (OP).

We followed 1 516 392 individuals from the Swedish population born 1980–2000, from 1 July 2007, until 31 Dec 2017. We examined putative risk predictors with univariable and multivariable Cox Models and the potential causal effects of predictors by propensity score and co-sibling analyses.

Of the individuals in our cohort, 24.8% (375 404) received a first OP, of whom 3034 (0.90%) developed a subsequent first OUD. The hazard ratio (HR) (± 95% CIs) for OUD after OP equaled 7.10 (6.75–7.46), with a mean time to onset of 3.41 (2.39) years. The strongest putative risk factors for development of OUD after OP were prior psychiatric and substance use disorders, criminal behavior, parental divorce/death, poor school performance, current community deprivation, divorce, and male sex. Few predictors differed across sexes. OP renewal was associated with a HR of 3.66 (3.41–3.93) for OUD. Co-sibling and propensity score analyses suggested that at least a moderate proportion of the risk factor-OUD association was likely causal. A risk score to predict OUD after OP had an AUC of 0.85, where nearly 60% of cases scoring in the top decile.

In a general population sample, an OP represents a substantial risk factor for subsequent OUD. Many of the risk factors for OUD after OP can be readily assessed at the time of potential OP, permitting clinicians to evaluate the risk of iatrogenic OUD.

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.

Major depressive disorder (MDD) is one of the growing human mental health challenges facing the global health care system. In this study, the structural connectivity between symptoms of MDD is explored using two different network modeling approaches.

Data are from ‘the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD)’. A cohort of N = 2163 American Caucasian female-female twins was assessed as part of the VATSPSUD study. MDD symptoms were assessed using personal structured clinical interviews. Two network analyses were conducted. First, an undirected network model was estimated to explore the connectivity between the MDD symptoms. Then, using a Bayesian network, we computed a directed acyclic graph (DAG) to investigate possible directional relationships between symptoms.

Based on the results of the undirected network, the depressed mood symptom had the highest centrality value, indicating its importance in the overall network of MDD symptoms. Bayesian network analysis indicated that depressed mood emerged as a plausible driving symptom for activating other symptoms. These results are consistent with DSM-5 guidelines for MDD. Also, somatic weight and appetite symptoms appeared as the strongest connections in both networks.

We discuss how the findings of our study might help future research to detect clinically relevant symptoms and possible directional relationships between MDD symptoms defining major depression episodes, which would help identify potential tailored interventions. This is the first study to investigate the network structure of VATSPSUD data using both undirected and directed network models.

Among individuals with alcohol use disorder (AUD) and drug use disorder (DUD), is their genetic liability and its specificity moderated by substance availability?

Offspring (born 1960–1995) and their biological parents from three family types [not-lived-with (NLW) biological father, mother and adoptive] and their AUD and DUD diagnoses were ascertained from Swedish national registers. Parent–offspring resemblance was calculated by tetrachoric correlation.

In Swedes born from 1960 to 1995, prevalence rates of AUD were stable while DUD rates increased substantially. Best-estimate tetrachoric correlations (±95% confidence intervals) between AUD in biological parents and AUD and DUD in their offspring were, respectively, +0.19 (0.18–0.20) and +0.18 (0.17–0.20). Parallel results from DUD in parents to AUD and DUD in children were +0.12 (0.10–0.13) and +0.27 (0.26–0.28). When divided into older and younger cohorts, the specificity of DUD transmission increased substantially over time, while the genetic correlation between AUD and DUD significantly decreased.

Raised when alcohol was the preferred substance of abuse and illicit drugs highly stigmatized, AUD in parents reflected a general liability to substance use disorders, as they transmitted similar genetic risk for AUD and DUD to their children raised when both substances were widely available and relatively acceptable. DUD in parents, by contrast, reflected a more specific liability to DUD and, when transmitted to offspring, produced a considerably stronger risk for DUD than for AUD that increased over time. The magnitude and specificity of the genetic liability to psychoactive substances can be influenced by the availability of that substance.

Previous studies have found that stressful life events (SLEs) are associated with an increased risk of adult depression. However, many studies are observational in nature and limited by methodological issues, such as potential confounding by genetic factors. Genetically informative research, such as the co-twin control design, can strengthen causal inference in observational studies. Discrete-time survival analysis has several benefits and multilevel survival analysis can incorporate frailty terms (random effects) to estimate the components of the biometric model. In the current study, we investigated associations between SLEs and depression risk in a population-based twin sample (N = 2299).

A co-twin control design was used to investigate the influence of the occurrence of SLEs on depression risk. The co-twin control design involves comparing patterns of associations in the full sample and within dizygotic (DZ) and monozygotic twins (MZ). Associations were modelled using discrete-time survival analysis with biometric frailty terms. Data from two time points were used in the analyses. Mean age at Wave 1 was 28 years and mean age at Wave 2 was 38 years.

SLE occurrence was associated with increased depression risk. Co-twin control analyses indicated that this association was at least in part due to the causal influence of SLE exposure on depression risk for event occurrence across all SLEs and for violent SLEs. A minor proportion of the total genetic risk of depression reflected genetic effects related to SLEs.

The results support previous research in implicating SLEs as important risk factors with probable causal influence on depression risk.

The authors sought to clarify the impact of spousal psychiatric disorders of differing severity [major depression or anxiety disorders (DAD) v. bipolar disorder or nonaffective psychosis (BPN)] on proband risk for alcohol use disorder (AUD) during marriage.

In a Swedish cohort (N = 744 628), associations between spousal DAD and BPN and proband AUD were estimated with Cox proportional hazards; associations between parental AUD, proband premarital AUD, and spousal lifetime DAD and BPN were estimated with logistic regression; and whether spousal DAD or BPN causally increased risk for AUD was evaluated with frailty models.

Spousal premarital DAD, spousal marital-onset DAD, and spousal BPN (premarital or marital-onset) were associated with proband AUD during marriage [hazard ratios (HR) range 1.44–3.72]. Those with a parental or premarital history of AUD (v. without) were more likely to marry a spouse with DAD or BPN (odds ratios 1.22–2.77). Moving from an unaffected first spouse to a DAD-affected second spouse increased AUD risk in males (HR 2.90). Moving from an unaffected first spouse to a BPN-affected second spouse increased AUD risk (HRmales 3.96; HRfemales 5.64). Moving to an unaffected second spouse from a DAD-affected first spouse decreased AUD risk, with stronger evidence in females compared to males (HRmales 0.59; HRfemales 0.28).

Associations between spousal DAD or BPN and proband AUD reflect both selection and causal effects. Marriage to a BPN-affected spouse has a particularly strong effect on AUD risk, with more modest effects for spousal DAD.

Despite a large descriptive literature linking creativity and risk for psychiatric illness, the magnitude and specificity of this relationship remain controversial.

We examined, in 1 137 354 native Swedes with one of 59 3-digit official and objective occupational codes in managerial and educated classes, their familial genetic risk score (FGRS) for ten major disorders, calculated from 1st through 5th degree relatives. Mean FGRS across disorders were calculated, in 3- and 4-digit occupational groups, and then controlled for those whose disorder onset preceded occupational choice. Using sequential analyses, p values were evaluated using Bonferroni correction.

3-digit professions considered to reflect creativity (e.g. ‘artists’ and ‘authors’) were among those with statistically significant elevations of FGRS. Among more specific 4-digit codes, visual artists, actors, and authors stood out with elevated genetic risks, highest for major depression (MD), anxiety disorders (AD) and OCD, more modest for bipolar disorders (BD) and schizophrenia and, for authors, for drug and alcohol use disorders. However, equal or greater elevations in FGRS across disorders were seen for religious (e.g. ministers), helping (e.g. psychologists, social workers), and teaching/academic occupations (e.g. professors). The potential pathway from FGRS → Disorder → Occupation accounts for a modest proportion of the signal, largely for MD and AD risk.

While traditional creative occupations were associated with elevated genetic risk for a range of psychiatric disorders, this association was not unique, as similar, or greater elevations were seen for religious, helping and teaching professions and was stronger for internalizing than psychotic disorders.

Functional somatic disorders (FSD) feature medical symptoms of unclear etiology. Attempts to clarify their origin have been hampered by a lack of rigorous research designs. We sought to clarify the etiology of the FSD by examining the genetic risk patterns for FSD and other related disorders.

This study was performed in 5 829 186 individuals from Swedish national registers. We quantified familial genetic risk for FSD, internalizing disorders, and somatic disorders in cases of chronic fatigue syndrome (CFS), fibromyalgia (FM), and irritable bowel syndrome (IBS), using a novel method based on aggregate risk in first to fifth degree relatives, adjusting for cohabitation. We compared these profiles with those of a prototypic internalizing psychiatric – major depression (MD) – and a somatic/autoimmune disorder: rheumatoid arthritis (RA).

Patients with FM carry substantial genetic risks not only for FM, but also for pain syndromes and internalizing, autoimmune and sleep disorders. The genetic risk profiles for IBS and CFS are also widely distributed although with lower average risks. By contrast, genetic risk profiles of MD and RA are much more restricted to related conditions.

Patients with FM have a relatively unique family genetic risk score profile with elevated genetic risk across a range of disorders that differs markedly from the profiles of a classic autoimmune disorder (RA) and internalizing disorder (MD). A similar less marked pattern of genetic risks was seen for IBS and CFS. FSD arise from a distinctive pattern of genetic liability for a diversity of psychiatric, autoimmune, pain, sleep, and functional somatic disorders.

Do genetic risk profiles for drug use disorder (DUD), major depression (MD), and attention-deficit hyperactivity disorder (ADHD) differ substantially as a function of sex, age at onset (AAO), recurrence, mode of ascertainment, and treatment?

Family genetic risk scores (FGRS) for MD, anxiety disorders, bipolar disorder, schizophrenia, alcohol use disorder, DUD, ADHD, and autism-spectrum disorder were calculated from 1st–5th degree relatives in the Swedish population born 1932–1995 (n = 5 829 952). Profiles of these FGRS were obtained and compared across various subgroups of DUD, MD, and ADHD cases.

Differences in FGRS profiles for DUD, MD, and ADHD by sex were modest, but they varied substantially by AAO, recurrence, ascertainment, and treatment with scores typically higher in cases with greater severity (e.g. early AAO, high recurrence, ascertainment in high intensity clinical settings, and treatment). However, severity was not always related to purer genetic profiles, as genetic risk for many disorders often increased together. However, some results, such as by mode of ascertainment from different Swedish registries, produced qualitative differences in FGRS profiles.

Differences in FGRS profiles for DUD, MD, and ADHD varied substantially by AAO, recurrence, ascertainment, and treatment. Replication of psychiatric studies, particularly those examining genetic factors, may be difficult unless cases are matched not only by diagnosis but by important clinical characteristics. Genetic correlations between psychiatric disorders could arise through one disorder impacting on the patterns of ascertainment for the other, rather than from the direct effects of shared genetic liabilities.

Does the genetic aptitude for educational attainment (GAEA) moderate the genetic risk for alcohol use disorder (AUD) and drug use disorder (DUD)?

In the native Swedish population, born 1960–1980 and followed through 2017 (n = 1 862 435), the family genetic risk score (FGRS) for AUD and DUD and GAEA were calculated from, respectively, the educational attainment and risk for AUD and DUD, of 1st through 5th degree relatives from Swedish national registers. Analyses utilized Aalen's linear hazards models.

Risk for AUD was robustly predicted by the main effects of FGRSAUD [b = 6.32 (95% CI 6.21–6.43), z = 64.9, p < 0.001) and GAEA [b = −2.90 (2.83–2.97), z = 44.1, p < 0.001] and their interaction [b = −1.93 (1.83–2.03), z = 32.9, p < 0.001]. Results were similar for the prediction of DUD by the main effects of FGRSDUD [b = 4.65 (CI 4.56–4.74), z = 59.4, p < 0.001] and GAEA [−2.08 (2.03–2.13), z = 46.4, p < 0.001] and their interaction [b = −1.58 (1.50–1.66)), z = 30.2, p < 0.001]. The magnitude of the interactions between GAEA and FGRSAUD and FGRSDUD in the prediction of, respectively, AUD and DUD was attenuated only slightly by the addition of educational attainment to the model.

The genetic propensity to high educational attainment robustly moderates the genetic risk for both AUD and DUD such that the impact of the genetic liability to AUD and DUD on the risk of illness is substantially attenuated in those with high v. low GAEA. This effect is not appreciably mediated by the actual level of educational attainment. These naturalistic findings could form the basis of prevention efforts in high-risk youth.

– Comorbidity between psychiatric disorders is extensive but, from a genetic perspective, still poorly understood. Modern molecular genetic approaches to this problem are limited by a reliance on case–control designs.

– In 5 828 760 individuals born in Sweden from 1932–1995 with a mean (s.d.) age at follow-up of 54.4 (18.1), we examined family genetic risk score (FGRS) profiles including internalizing, psychotic, substance use and developmental disorders in 10 pairs of psychiatric and substance use disorders diagnosed from population registries. We examined these profiles in three groups of patients: disorder A only, disorder B only and comorbid cases with both disorders.

– The most common pattern of findings, seen in five pairings, was simple and quantitative. Comorbid cases had higher FGRS than both non-comorbid cases for all (or nearly all) disorders. However, the pattern was more complex in the remaining five pairings and included qualitative changes where the comorbid cases showed no increases in FGRS for certain disorders and in a few cases significant decreases. Several comparisons showed an asymmetric pattern of findings with increases, in comorbidity compared to single disorder cases, of the FGRS for only one of the two disorders.

– The examination of FGRS profiles in general population samples where all disorders are assessed in all subjects provides a fruitful line of inquiry to understand the origins of psychiatric comorbidity. Further work will be needed, with an expansion of analytic approaches, to gain deeper insights into the complex mechanisms likely involved.

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.

Alcohol use disorder (AUD) is clinically heterogeneous. We examine its potential genetic heterogeneity as a function of sex, age, clinical features and mode of ascertainment.

In the Swedish population born 1932–1995 (n = 5 829 952), we examined the genetic risk profiles for AUD, major depression (MD), anxiety disorders, bipolar disorder, drug use disorder (DUD), attention deficit-hyperactivity disorder (ADHD) and criminal behavior (CB) in 361 124 cases of AUD subdivided by sex, age at onset (AAO), recurrence, mode of ascertainment and medical complications. Family genetic risk scores (FGRS), calculated from 1st to 5th-degree relatives controlling of cohabitation, assesses genetic risk from phenotypes in the family, not from DNA variants.

FGRS profiles differed modestly across sex with all scores higher in females. Differences were more pronounced for AAO and recurrence with the FGRS for AUD, DUD, ADHD and CB substantially higher in cases with early AAO or high recurrence rates. Genetic profiles differed considerably by mode of ascertainment, with higher FGRS for AUD and most other disorders in patients seen in hospital v. primary care settings. Cases of AUD with medical complications had higher FGRS for AUD. AUD cases comorbid with MD and DUD had higher FGRS risk for AUD, but this genetic may be less specific given increases in FGRS for multiple other disorders.

From a genetic perspective, AUD differs substantially as a function of AAO, recurrence, mode of ascertainment and patterns of comorbidity, suggesting caution in cross-sample comparisons of AUD cohorts that differ in these features.

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.