Polygenic risk for suicide attempt is associated with lifetime suicide attempt in US soldiers independent of parental risk

Abstract

Background:

Suicide is a leading cause of death worldwide. Whereas some studies have suggested that a direct measure of common genetic liability for suicide attempts (SA), captured by a polygenic risk score for SA (SA-PRS), explains risk independent of parental history, further confirmation would be useful. Even more unsettled is the extent to which SA-PRS is associated with lifetime non-suicidal self-injury (NSSI).

Methods:

We used summary statistics from the largest available GWAS study of SA to generate SA-PRS for two non-overlapping cohorts of soldiers of European ancestry. These were tested in multivariable models that included parental major depressive disorder (MDD) and parental SA.

Results:

In the first cohort, 417 (6.3 %) of 6573 soldiers reported lifetime SA and 1195 (18.2 %) reported lifetime NSSI. In a multivariable model that included parental history of MDD and parental history of SA, SA-PRS remained significantly associated with lifetime SA [aOR = 1.26, 95%CI:1.13–1.39, p < 0.001] per standardized unit SA-PRS]. In the second cohort, 204 (4.2 %) of 4900 soldiers reported lifetime SA, and 299 (6.1 %) reported lifetime NSSI. In a multivariable model that included parental history of MDD and parental history of SA, SA-PRS remained significantly associated with lifetime SA [aOR = 1.20, 95%CI: 1.04–1.38, p = 0.014]. A combined analysis of both cohorts yielded similar results. In neither cohort or in the combined analysis was SA-PRS significantly associated with NSSI.

Conclusions:

PRS for SA conveys information about likelihood of lifetime SA (but not NSSI, demonstrating specificity), independent of self-reported parental history of MDD and parental history of SA.

Limitations:

At present, the magnitude of effects is small and would not be immediately useful for clinical decision-making or risk-stratified prevention initiatives, but this may be expected to improve with further iterations. Also critical will be the extension of these findings to more diverse populations.

1. Introduction

Suicide is a serious global societal and public health problem (Lovero et al., 2023). In the United States in 2021, suicide was the ninth leading cause of death, and the second leading cause of death for individuals between the ages of 10–14 and 25–34 (Center for Disease Control CDC, 2023). Additionally, concern about suicide has raised alarms in the US military, where from 2014 to 2019, the suicide death rate for the Active Component increased from 20.4 to 25.9 suicides per 100,000 Service members (Department of Defense, 2020). Despite a great deal of research into risk factors (Holliday et al., 2020) and substantial investments in suicide prevention (Stein et al., 2019; Curley et al., 2020), it remains uncertain why suicidality has trended higher. These observations have called for the development of better predictive models that can help target those individuals at highest risk (Kessler et al., 2020).

An emerging body of research has extended the search for suicide risk factors to include genetic risk. Twin studies had initially set the stage for expecting to find specific genetic risk factors, providing heritability estimates of 30–55 % (Tidemalm et al., 2011). It is now clear that suicidal behaviors are genetically complex – as are most neuropsychiatric traits (Wendt et al., 2020) – and the evidence suggests that many common variants, each of small effect, contribute to risk (with the possibility that rare variants confer greater risk) (Sokolowski and Wasserman, 2020).

Epidemiological studies have shown that risk factors for various aspects of self-harm (i.e., ideation, attempts, and deaths) overlap only partially (Nock et al., 2013; Naifeh et al., 2020). This awareness has carried over to the genetic epidemiological study of self-harm where, increasingly, studies are each centered on one stage or type of self-harm (e.g., suicide ideation; suicide attempts; violent suicide attempts; suicide deaths).

Early genetic studies of suicidality, including our own genome-wide association study (GWAS) of suicide attempts in US Army soldiers (Stein et al., 2017), were underpowered (Mirkovic et al., 2016). More recent GWAS of suicide attempts, which have achieved much larger sample sizes thanks to data-sharing within and across consortia, have emphasized a genetic correlation between major depressive disorder (MDD) and SA (Mullins et al., 2019; Levey et al., 2019; Mullins et al., 2022). Similar conclusions were reached from a GWAS of death by suicide, which found a polygenic association with MDD (and several other behavioral traits phenotypically linked with suicide deaths) (Docherty et al., 2020). Our work has shown a polygenic association between MDD and SA in U.S. Army soldiers (Stein et al., 2021), consistent with findings that polygenic risk for MDD was associated with SA in adults across 4 clinical samples (Fanelli et al., 2022) and with suicidal behaviors in preadolescent youths (Joo et al., 2022).

Given the recent completion of the largest available GWAS metaanalysis of SA (Docherty et al., 2023), we asked two questions: (Lovero et al., 2023) whether polygenic risk of SA, per se, is predictive of lifetime SA in two independent cohorts of US Army soldiers, over and above the robust risks associated with parental history of SA (or suicide death) (Wang et al., 2022) and parental history of MDD; and (Center for Disease Control CDC, 2023) whether polygenic risk of SA is predictive of lifetime non-suicidal self-injury (NSSI), which has epidemiological similarities and differences from SA. The first question has been addressed in recent studies showing an independent association of polygenic risk for SA on suicidal thoughts and behaviors in children (Lee et al., 2022) and suicide attempts in adolescents (Barzilay et al., 2022), but we believe this to be the first replication of these findings in an adult sample. The second question has been addressed in a report from the Collaborative Study on the Genetics of Alcoholism (COGA) where it was shown that NSSI was less strongly genetically related to SA than were other forms of suicidal thoughts and behaviors (Colbert et al., 2023). To the best of our knowledge, that finding has yet to be replicated.

In the present study, we used data from two non-overlapping cohorts evaluated in the Army Study to Assess Risk and Resilience in Servicemembers (STARRS) (Naifeh et al., 2019) to answer these questions.

2. Methods

2.1. Subjects

Data come from two components of Army STARRS: the New Soldier Study (NSS) and the Pre/Post Deployment Study (PPDS). Detailed information about the design and conduct of STARRS is available in a separate report (Ursano et al., 2014). Soldiers from the respective studies described below are nonoverlapping as confirmed by genetic analysis.

Cohort 1: New Soldier Study (NSS).

The NSS was carried out among new soldiers at the start of their basic training at three Army Installations between April 2011 and November 2012. Of 39,784 NSS respondents who completed the Self-Administered Questionnaire (SAQ), 33,088 (83.2 %) provided blood samples. Funding constraints led us to genotype a subset of respondents that would be optimally informative for the aims of STARRS: All cases of reported lifetime SA and PTSD were genotyped, as were a set of controls stratum-matched on sex, service type (Regular Army vs. Guard/Reserve), and childhood adversity quartile. The NSS analyses described herein include 6573 soldiers of European ancestry with available survey and genotype data (see below).

Cohort 2: Pre/Post Deployment Study (PPDS).

The PPDS collected baseline data (also using a version of the SAQ) from US Army soldiers in three Brigade Combat Teams during the first quarter of 2012, within approximately six weeks of their upcoming deployment to Afghanistan. A total of 9949 Soldiers were present for duty in the three Brigade Combat Teams; 9488 (95.3 %) consented to participate in the survey with 8558 (86.0 %) providing complete baseline survey responses and consent to link their survey responses to their administrative records. The PPDS analyses described herein include 4900 soldiers of European ancestry with available survey and genotype data (see below).

2.2. Measures

The SAQ surveyed socio-demographic characteristics, lifetime and past-30-day mental disorders, and an array of potential risk and resilience factors.

Suicide Attempt and Non-Suicidal Self-Injury Assessment.

Suicidal behaviors were assessed using an adaptation of the Columbia Suicidal Severity Rating Scale (Posner et al., 2011). Pertinent to the data presented here, all respondents were asked if they had a history of SA (“Did you ever make a suicide attempt [i.e., purposefully hurt yourself with at least some intention to die]?”). All respondents were also asked if they had a history of non-suicidal self-injury (NSSI) (”Did you ever do something to hurt yourself on purpose, but without wanting to die [e.g., cutting yourself, hitting yourself, or burning yourself]?”).

This information was available at baseline for NSS and PPDS, and at approximately 6- and 9-months post index deployment for PPDS. It was also available at later dates for those NSS and PPDS soldiers who subsequently took part in a 6- to 8-year follow-up survey referred to as STARRS-LS (STARRS Longitudinal Study), for which data collection began 12 September 2016 and is ongoing; data included here are for assessments obtained through 10 April 2018. The STARRS-LS survey was conducted using a mixed-mode design, with participants given the option of completing the interview as a self-administered survey on the web, or with an interviewer over the telephone. This self-report information on suicidality was complemented by access to Army health records where SA(s) were recorded if medical attention was sought. For the analyses presented here, cases are soldiers with a lifetime history of SA (from either self-report [non-fatal attempts] or Army health records [fatal or non-fatal attempts]) and controls are those individuals with no lifetime history of SA.

Parental History of Major Depressive Disorder.

The Army STARRS surveys queried parental history of MDD separately for the respondent’s biological mother and father. The survey item (“Did any of them ever have times lasting two weeks or longer when they were so depressed they couldn’t concentrate, felt worthless, or felt their life was not worth living?“) was derived from the Family History Screen (Weissman et al., 2000). An affirmative response for either (or both) parent(s) was considered as YES for parental MDD.

Parental History of Suicide Attempt or Death.

The Army STARRS surveys queried parental history of SA (or suicide death) asking whether, during the respondent’s childhood, “A parent attempted suicide”, or “A parent committed suicide”. An affirmative response to either (for one or both parents) was coded as YES for parental SA.

2.3. Genetic data collection and procedures

Samples were genotyped using either the Illumina OmniExpress + Exome array with additional custom content or the Ilumina PsychChip. Quality control (QC) of genotype data used standard protocols as described elsewhere (Stein et al., 2016). Relatedness testing was carried out with PLINK v1.90 (Chang et al., 2015) and, for pairs of subjects with π of >0.2, one member of each relative pair was removed at random.

Genotype imputation was performed with a 2-step pre-phasing/imputation approach with a multi-ancestry reference panel from 1000 Genomes Project (August 2012 phase 1 integrated release; 2186 phased haplotypes with 40,318,245 variants). We removed SNPs that were not present in the 1000 Genomes Project reference panel, had non-matching alleles to 1000 Genome Project reference, or with ambiguous, unresolvable alleles (AT/GC SNPs with minor allele frequency [MAF] > 0.1). A total of 664,457 SNPs for the Illumina OmniExpress array and 360,704 for the Illumina PsychChip entered the imputation. We performed the following QC procedures to obtain the genotype data for population assignment and principal components analysis (PCA). We retained autosomal SNPs with missing rate < 0.05; samples with individual-wise missing rate < 0.02; SNPs with missing rate < 0.02; and SNPs with missing rate difference between cases and controls <0.02. After QC, we merged our study samples with HapMap3 samples. We retained SNPs with MAF ≥ 0.01 and performed LD pruning at R² > 0.02. Finally, we excluded SNPs in MHC region (Chr 6:25-35 Mb) and Chr 8 inversion (Chr 8:7-13 Mb). Population (ancestry) assignment was conducted using standard methods (see (Stein et al., 2017) for details).

Polygenic Risk Scores (PRS) computation.

PRS for the SA phenotype were computed using PRS-CS-auto, a method that uses a Bayesian regression framework and places a continuous shrinkage prior on the effects sizes of SNPs in the discovery GWAS summary statistics (Ge et al., 2019). PLINK 2.0 (Chang et al., 2015) was used to weight all SNPs by their effect sizes calculated using PRS-CS-auto and sum all SNPs into PRS for each individual in the target cohort. PRS analyses were conducted only in the European ancestry subsamples because of the unavailability of reference GWAS data for other populations (Choi et al., 2020; Peterson et al., 2019). Summary statistics from the International Suicide Genetics Consortium-Million Veteran Program (ISGHC-MVP) meta-analysis (doi.org/10.1101/2022.07.03.22277199) (Docherty et al., 2023) with Army STARRS data withheld (N = 35,116 cases, 768,755 controls) were used as the discovery GWAS; 1000 Genomes European was used as the LD reference panel. PRS were standardized within each study (NSS and PPDS) for the analysis.

2.4. Statistical analysis

Multivariable logistic regression models were performed to assess the association of SA-PRS, parental history of MDD, and parental history of SA with lifetime SA and NSSI, controlling for the top 10 ancestral principal components, age, batch (for NSS, which had been genotyped in two batches) and sex. Additional models included personal history of MDD (lifetime and past-30-day). Adjusted odds ratios (aOR) were reported with 95 % confidence intervals. Nagelkerke’s pseudo-R-square was reported for models. Likelihood ratio test (LRT) was used to examine whether adding the SA-PRS improved model prediction. All analyses were conducted in R version 3.6.1.

3. Results

3.1. Findings in New Soldier Study (NSS)

The NSS sample consisted of 417 lifetime SA cases (6.3 %) and 6156 controls with no history of lifetime SA; and 1195 lifetime NSSI cases (18.2 %) and 5378 controls with no history of lifetime NSSI. The sample was 15 % female. Mean age of the sample was 20.8 (SD 3.3) years; median = 20 years, interquartile range: 19–22 years. 1086 (17.0 % of) soldiers had a lifetime history of MDD and 532 (8.4 %) had a past-30-day history of MDD. 2107 (32.1 %) soldiers reported a parental history of MDD and 553 (8.4 %) reported a parental history of SA (Table 1, top).

Table 1.

Personal (Lifetime) and parental histories of soldiers in each study.

	Yes	No
New Soldier Study
Lifetime Suicide Attempt	417 (6.3 %)	6156 (93.7 %)
Lifetime Non-Suicidal Self-Injury	1195 (18.2 %)	5378 (81.8 %)
Lifetime MDD	1086 (17.0 %)	5288 (83.0 %)
Past-30-Day MDD	532 (8.4 %)	5842 (91.7 %)
Parental History of Major Depression	2107 (32.1 %)	4466 (67.9 %)
Parental History of Suicide Attempt or Death	553 (8.4 %)	6020 (91.6 %)
Pre-Post Deployment Study
Lifetime Suicide Attempt	204 (4.2 %)	4696 (95.8 %)
Lifetime Non-Suicidal Self-Injury	299 (6.1 %)	4601 (93.9 %)
Lifetime MDD	551 (11.2 %)	4349 (88.8 %)
Past-30-Day MDD	310 (6.3 %)	4590 (93.7 %)
Parental History of Major Depression	958 (19.6 %)	3942 (80.5 %)
Parental History of Suicide Attempt or Death	218 (4.5 %)	4682 (95.6 %)

In a multivariable model that included age, sex, 10 ancestral PCs, and batch, the SA-PRS was significantly associated with lifetime history of SA (adjusted odds ratio (aOR) = 1.27 [95 % CI: 1.15–1.41] per SD increase in SA-PRS). SA-PRS continued to be significantly associated with lifetime SA (aOR = 1.26 [95 % CI: 1.13–1.39]) in a multivariable model that included all of the aforementioned predictors and added parental history of MDD (aOR = 1.57 [95 % CI: 1.26–1.96]) and parental history of SA (aOR = 1.48 [95 % CI: 1.09–2.02]). (Table 2, top). This model explained significantly more of the variance in the lifetime SA outcome than a model that did not include SA-PRS (pseudo-R-square = 4.5 % vs 3.7 %, LRT p = 0.0002).

Table 2.

Multivariable model for lifetime suicide attempt and lifetime non-suicidal self-injury in New Soldier Study (NSS)^*

	Adjusted Odds Ratio (aOR)	aOR 95 % CI	p-value
Lifetime Suicide Attempt (SA)
Parental Major Depression	1.57	1.26–1.96	<0.001
Parental Suicide Attempt or Death	1.48	1.09–2.02	0.0134
Suicide Attempt Polygenic Risk Score (SA-PRS)	1.26	1.13–1.39	<0.001
Lifetime Non-Suicidal Self-Injury (NSSI)
Parental Major Depression	1.67	1.45–1.92	<0.001
Parental Suicide Attempt or Death	1.25	1.003–1.55	0.047
Suicide Attempt Polygenic Risk Score (SA-PRS)	0.99	0.93–1.06	0.841

^*Models also include the following covariates (not shown in tables): age (years), sex, batch, and 10 principal components of ancestry.

In a multivariable model that included age, sex, 10 ancestral PCs, and batch, the SA-PRS was not significantly associated with lifetime history of NSSI (aOR = 1.01 [95 % CI: 0.94–1.07]). Neither was SA-PRS significantly associated with lifetime history of NSSI (aOR = 0.99 [95 % CI: 0.93–1.06]) in a multivariable model that included all of the aforementioned predictors and added parental history of MDD (aOR = 1.67 [95 % CI: 1.45–1.92]) and parental history of SA (aOR = 1.25 [95 % CI: 1.00–1.55]). (Table 2, bottom).

3.2. Replication in Pre-Post Deployment Study (PPDS)

The PPDS sample consisted of 204 lifetime SA cases (4.2 %) and 4696 controls with no history of lifetime SA; and 299 lifetime NSSI cases (6.1 %) and 4601 controls with no history of lifetime NSSI. The sample was 4 % female, reflecting the overwhelming male majority deployed to combat at the time of the survey. Mean age was 25.9 (SD 5.9) years; median = 24 years, interquartile range: 21–29 years. 551 (11.2 % of) soldiers had a lifetime history of MDD and 310 (6.3 %) had a pst-30-day history of MDD. 958 (19.6 % of) soldiers reported a parental history of MDD and 218 (4.5 %) reported a parental history of suicide attempt or death (Table 1, bottom).

In a multivariable model that included age, sex, and 10 ancestral PCs, the SA-PRS was significantly associated with lifetime history of SA (aOR = 1.22 [95 % CI: 1.06–1.41] per SD increase in SA-PRS). SA-PRS continued to be significantly associated with lifetime SA (aOR = 1.20 [95 % CI: 1.04–1.38]) in a multivariable model that included all of the aforementioned predictors and added parental history of MDD (aOR = 1.89 [95 % CI: 1.36–2.61]) and parental history of SA (aOR = 1.53 [95 % CI: 0.90–2.59]) (Table 3, top). This model explained significantly more of the variance in the lifetime SA outcome than a model that did not include SA-PRS (pseudo-R-square = 3.6 % vs 3.2 %, LRT p = 0.014).

Table 3.

Multivariable model for lifetime suicide attempt and lifetime non-suicidal self-injury in Pre-Post Deployment Study (PPDS)^*.

	Adjusted Odds Ratio (aOR)	aOR 95 % CI	p-value
Lifetime Suicide Attempt (SA)
Parental Major Depression	1.89	1.36–2.61	<0.001
Parental Suicide Attempt or Death	1.53	0.90–2.59	0.113
Suicide Attempt Polygenic Risk Score (SA-PRS)	1.20	1.04–1.04	0.014
Lifetime Non-Suicidal Self-Injury (NSSI)
Parental Major Depression	2.69	2.07–3.50	<0.001
Parental Suicide Attempt or Death	1.15	0.72–1.81	0.563
Suicide Attempt Polygenic Risk Score (SA-PRS)	1.06	0.94–1.20	0.336

^*Models also include the following covariates (not shown in tables): age (years), sex, and 10 principal components of ancestry.

In a multivariable model that included age, sex, and 10 ancestral PCs, the SA-PRS was not significantly associated with lifetime history of NSSI (aOR = 1.09 [95 % CI: 0.97–1.23]). Neither was SA-PRS significantly associated with lifetime history of NSSI (aOR = 1.06 [95 % CI: 0.94–1.20]) in a multivariable model that included all of the aforementioned predictors and added parental history of MDD (aOR = 2.69 [95 % CI: 2.07–3.50]) and parental history of SA (aOR = 1.15 [95 % CI: 0.72–1.81]). (Table 3, bottom).

3.3. Combined sample

In the combined sample consisting of soldiers from both cohorts (N = 11,473) a multivariable model that included age, sex, cohort, 10 ancestral PCs, parental history of MDD, and parental history of SA, SA-PRS was significantly associated with lifetime history of SA (aOR = 1.23 [95 % CI: 1.13–1.34] per SD increase in SA-PRS). This model explained significantly more (15.6 %; p < 0.000001) of the variance in the lifetime SA outcome than a model that did not include SA-PRS. In a multivariable model that included all of the aforementioned predictors in addition to the soldier’s lifetime history of MDD (positive in 1637 [14.52 %] of soldiers) and past-30-day history of MDD (positive in 842 [7.47 %] of soldiers) the association of SA-PRS with lifetime SA was largely unchanged (aOR = 1.21 [95 % CI: 1.11–1.32]).

In none of the above models was SA-PRS significantly associated with lifetime NSSI.

4. Discussion

Among the numerous potential applications of polygenic risk scores (PRS) is their use to stratify individuals based on their predicted risk for a range of mental and physical health outcomes (Polygenic Risk Score Task Force of the International Common Disease A, 2021; Wray et al., 2021; Murray et al., 2020). A suicidality PRS has been shown to be associated with suicidal thoughts and behaviors in a recent study of US military veterans, providing proof-of-concept for their usefulness in this regard (Nichter et al., 2023). Previous studies have shown that genetic liability for MDD is associated with risk for SA (Mullins et al., 2019; Levey et al., 2019; Mullins et al., 2014; Ruderfer et al., 2020) as well as for suicide death (Docherty et al., 2020).

In this study of two non-overlapping cohorts of United States Army soldiers, and in the combined sample, we found polygenic risk for suicide attempt (SA-PRS) was associated with lifetime risk of suicide attempt (SA) as determined from a combination of self-report and Army medical records. We were able to show that SA-PRS added to the predictive utility of two readily obtainable self-report parameters of SA risk, parental history of MDD and parental history of SA (Andlauer et al., 2021). The findings were largely unchanged by the addition of personal lifetime and past-30-day history of MDD. These findings, which we believe to be the first in adults, are consistent with those emanating from two recent studies of children and adolescents, respectively (Lee et al., 2022; Barzilay et al., 2022).

Importantly, we found no association between SA-PRS and NSSI, supporting the notion that NSSI and SA have different underlying pre-dispositions. These findings are consistent with recent observations from COGA, where an NSSI PRS was relatively weakly genetically correlated with other PRS for suicidal thoughts and behaviors (including SA), and where a PRS for SA had relatively little predictive value for NSS (compared to other forms of suicidal thoughts and behaviors) (Colbert et al., 2023). Our results further strengthen the argument that not all types of suicidal thoughts and behaviors share the same underlying genetic etiology, and that NSSI is a good example of one such outlier.

Strengths of the study are the relatively large sample sizes, the use of the largest available GWAS on SA for computation of the PRS, the systematic ascertainment of SA through surveys and access to health records, and the ability to test for replication of findings across two cohorts. In this regard, it is of particular interest that the adjusted odds ratio (aOR) for SA-PRS predicting lifetime SA was very similar (aOR ~ 1.2) in both cohorts (and in the combined sample). A weakness is the possibility of incomplete ascertainment (e.g., if soldiers who left the Army were not part of STARRS-LS, and they attempted suicide after leaving the Army, they would be misclassified as controls), which would have biased findings toward the null. An additional weakness stems from the reliance on participant’s reporting of parental history of SA and depression, which may be inaccurate. Another potential weakness is that reports of SA by self-report and health record-reporting were not infrequently discordant, leaving open the possibility that additional reporting biases may have been operating. We chose to include either indication of SA for the outcome, to maximize sensitivity, considering that some SAs would only be ascertainable by self-report if medical attention was not sought. An additional potential shortcoming is that soldiers’ reporting of parental history may be inaccurate.

Another possible limitation is the distinction in methods used to ascertain lifetime history of non-suicidal self-injury (NSSI) and SA. For the former, we relied exclusively on self-report whereas for the latter we used a combination of self-report or medical records. This approach may have resulted in some misclassification for either outcome but is of even greater concern when relying solely on medical records (Randall et al., 2017).

This study was not designed to test if SA-PRS would predict new-onset SA among soldiers who did not report SA at baseline; the number of new-onset cases was insufficient to provide adequate statistical power for that analysis. Nevertheless, it will be crucial to demonstrate, in future prospective studies, whether SA- (or other) PRS offer predictive value in this regard. Lastly, our analyses focused solely on individuals of European ancestry (Peterson et al., 2019), given the known limitations of extending PRS from European to other ancestral groups. New approaches hold promise as a solution to this limitation (Marnetto et al., 2020; Hujoel et al., 2022; Ruan et al., 2022) and could be applied to this and other samples in the future.

Twin and other genetically informative studies suggest that SA is moderately (17 %) heritable (Fu et al., 2002), and that parental mental illness explains almost half of the genetic transmission of SA (Kendler et al., 2020). Studies of familial transmission of suicidal behavior have shown that in addition to parents, other first- and second-degree relatives contribute to familial risk, and it is likely that our SA-PRS is detecting some of this risk (Brent et al., 2015). The largest GWAS of SA to date has found a SNP-based heritability of approximately 6 % (Docherty et al., 2023). As genomic studies of suicide attempts increase in size and power, we expect that PRS for SA will incrementally improve in their predictive utility over and above other sociodemographic and life (and combat) stress measures that frequently enter into SA predictive models (Kessler et al., 2020). Recent GWAS findings related to suicidal thoughts and behaviors (Mirza et al., 2022; Kimbrel et al., 2022; Kimbrel et al., 2023) are also anticipated to result in PRS that can help with prediction of other important suicide-related traits beyond suicide attempts.

Much work needs to be done to demonstrate the clinical utility of PRS outside of the military setting. Given the magnitude of variance predicted by the current PRS, these are highly unlikely to be of clinical utility. Importantly, prospective longitudinal study designs are needed to determine if PRS can contribute to the prediction of new (or recurrent) suicide attempts. Given the fact that 50–60 % of people do not disclose their suicidal ideation and behavior to others (Hallford et al., 2023), PRS for SA may have a role to play in identifying those non-disclosing individuals at-risk for SA. Any applications of PRS for this purpose will need to tread carefully, balancing the ethical issues of an individual’s rights to privacy with medicine’s aims of preserving life (Docherty et al., 2021).

International Suicide Genetics Consortium and Suicide Working Group of the Psychiatric Genomics Consortium (members of both consortia are identical) consist of:

Anna R Docherty^1,2,3, Niamh Mullins^4,5, Allison E Ashley-Koch⁶, Xuejun Qin⁶, Jonathan R I Coleman^7,8, Andrey Shabalin^1,2, JooEun Kang⁹, Balasz Murnyak^1,2, Frank Wendt¹⁰, Mark Adams¹¹, Adrian I Campos^12,13, Emily DiBlasi^1,2, Janice M Fullerton^14,15, Henry R Kranzler^16,17, Amanda Bakian², Eric T Monson², Miguel E Rentería^12,18, Consuelo Walss-Bass¹⁹, Ole A Andreassen^20,21, Cynthia M Bulik^22,23,24, Howard J Edenberg^25,26, Ronald C Kessler²⁷, J John Mann²⁸, John I Nurnberger Jr^29,29, Giorgio Pistis³⁰, Fabian Streit³¹, Robert J Ursano³², Renato Polimonti¹⁰, Michelle Dennis³³, Melanie Garrett³⁴, Lauren Hair³⁵, Philip Harvey³⁶, Elizabeth R Hauser^6,37, Michael A Hauser⁶, Jennifer Huffman³⁸, Daniel Jacobson³⁹, Jennifer H Lindquist⁴⁰, Ravi Madduri⁴¹, Benjamin McMahon⁴², David W Oslin^43,44, Jodie Trafton⁴⁵, Swapnil Awasthi⁴⁶, Andrew W Bergen^47,48, Wade H Berrettini⁴⁹, Martin Bohus⁵⁰, Harry Brandt^51,52, Xiao Chang⁵³, Hsi-Chung Chen⁵⁴, Wei J Chen^54,55,56, Erik D Christensen^57,58, Steven Crawford^51,52, Scott Crow⁵⁹, Philibert Duriez^60,61, Alexis C Edwards³, Fernando Fernández-Aranda⁶², Manfred M Fichter^63,64, Olatunde Olayinka Ayinde⁶⁵, Hanga Galfalvy⁶⁶, Steven Gallinger⁶⁷, Michael Gandal⁶⁸, Philip Gorwood^60,61, Yiran Guo⁵³, Jonathan D Hafferty¹¹, Hakon Hakonarson^53,69, Katherine A Halmi⁷⁰, Akitoyo Hishimoto⁷¹, Sonia Jain⁷², Stéphane Jamain⁷³, Susana Jiménez-Murcia⁶², Craig Johnson⁷⁴, Allan S Kaplan^75,76,77, Walter H Kaye⁷⁸, Pamela K Keel⁷⁹, James L Kennedy^75,76,77, Minsoo Kim⁶⁸, Kelly L Klump⁸⁰, Daniel F Levey^81,82, Dong Li⁵³, Shih-Cheng Liao⁵⁴, Klaus Lieb⁸³, Lisa Lilenfeld⁸⁴, Adriana Lori⁸⁵, Pierre J Magistretti^86,87, Christian R Marshall⁸⁸, James E Mitchell⁸⁹, Richard M Myers⁹⁰, Satoshi Okazaki⁹¹, Ikuo Otsuka^66,91, Dalila Pinto^4,5, Abigail Powers⁸⁵, Nicolas Ramoz⁶¹, Stephan Ripke^46,92,93, Stefan Roepke⁹⁴, Vsevolod Rozanov^95,96, Stephen W Scherer^97,98, Christian Schmahl⁵⁰, Marcus Sokolowski⁹⁹, Anna Starnawska^{100,101,102,103}, Michael Strober^104,105, Mei-Hsin Su⁵⁶, Laura M Thornton²⁴, Janet Treasure^106,107, Erin B Ware^108,109, Hunna J Watson^24,110,111, Stephanie H Witt³¹, D Blake Woodside^{76,77,112,113}, Zeynep Yilmaz^24,114,115, Lea Zillich³¹, Rolf Adolfsson¹¹⁶, Ingrid Agartz^117,118,119, Tracy M Air¹²⁰, Martin Alda^121,122, Lars Alfredsson^123,124, Adebayo Anjorin¹²⁵, Vivek Appadurai^126,127, María Soler Artigas^{128,129,130,131}, Sandra Van der Auwera^132,133, M Helena Azevedo¹³⁴, Nicholas Bass¹³⁵, Claiton HD Bau^136,137, Bernhard T Baune^138,139, Frank Bellivier^{140,141,142,143}, Klaus Berger¹⁴⁴, Joanna M Biernacka¹⁴⁵, Tim B Bigdeli^3,146, Elisabeth B Binder^85,147, Michael Boehnke¹⁴⁸, Marco P Boks¹⁴⁹, Rosa Bosch^128,129,150, David L Braff¹⁵¹, Richard Bryant¹⁵², Monika Budde¹⁵³, Enda M Byrne^13,154, Wiepke Cahn¹⁵⁵, Miguel Casas^{128,129,131,150}, Enrique Castelao³⁰, Jorge A Cervilla¹⁵⁶, Boris Chaumette^157,158,159, Sven Cichon^{160,161,162,163}, Aiden Corvin¹⁶⁴, Nicholas Craddock¹⁶⁵, David Craig¹⁶⁶, Franziska Degenhardt¹⁶³, Srdjan Djurovic^167,168, Ayman H Fanous^3,146, Jerome C Foo¹⁶⁹, Andreas J Forstner^160,163,170, Mark Frye¹⁷¹, Justine M Gatt^14,152, Pablo V Gejman^172,173, Ina Giegling¹⁷⁴, Hans J Grabe^132,133, Melissa J Green^14,176, Eugenio H Grevet^177,178, Maria Grigoroiu-Serbanescu¹⁷⁹, Blanca Gutierrez¹⁸⁰, Jose Guzman-Parra¹⁸¹, Steven P Hamilton¹⁸², Marian L Hamshere¹⁶⁵, Annette M Hartmann¹⁷⁵, Joanna Hauser¹⁸³, Stefanie Heilmann-Heimbach¹⁶³, Per Hoffmann^161,162,163, Marcus Ising¹⁸⁴, Ian Jones¹⁶⁵, Lisa A Jones¹⁸⁵, Lina Jonsson¹⁸⁶, René S Kahn^5,187, John R Kelsoe^151,188, Kenneth S Kendler³, Stefan Kloiber^75,184,189, Karestan C Koenen^92,190,191, Manolis Kogevinas¹⁹², Bettina Konte¹⁷⁵, Marie-Odile Krebs^157,158,159, Mikael Landén^22,193, Jacob Lawrence¹⁹⁴, Marion Leboyer^195,196,197, Phil H Lee^92,93,198, Douglas F Levinson¹⁹⁹, Calwing Liao^200,201, Jolanta Lissowska²⁰², Susanne Lucae¹⁸⁴, Fermin Mayoral¹⁸¹, Susan L McElroy²⁰³, Patrick McGrath²⁰⁴, Peter McGuffin⁸, Andrew McQuillin¹³⁵, Divya Mehta^205,206, Ingrid Melle^20,207, Yuri Milaneschi²⁰⁸, Philip B Mitchell¹⁷⁶, Esther Molina²⁰⁹, Gunnar Morken^210,211, Preben Bo Mortensen^{101,114,127,212}, Bertram Müller-Myhsok^147,213,214, Caroline Nievergelt¹⁵¹, Vishwajit Nimgaonkar²¹⁵, Markus M Nöthen¹⁶³, Michael C O’Donovan¹⁶⁵, Roel A Ophoff^68,216, Michael J Owen¹⁶⁵, Carlos Pato^217,217, Michele T Pato²¹⁸, Brenda WJH Penninx²¹⁹, Jonathan Pimm¹³⁵, James B Potash²²⁰, Robert A Power^8,221,222, Martin Preisig³⁰, Digby Quested²²³, Josep Antoni Ramos-Quiroga^{128,129,131,150}, Andreas Reif²²⁴, Marta Ribasés^{128,129,130,131}, Vanesa Richarte^128,129,150, Marcella Rietschel²²⁵, Margarita Rivera^8,226, Andrea Roberts²²⁷, Gloria Roberts¹⁷⁶, Guy A Rouleau^228,229, Diego L Rovaris²³⁰, Dan Rujescu¹⁷⁵, Cristina Sánchez-Mora^{128,129,130,131}, Alan R Sanders^172,173, Peter R Schofield^14,15, Thomas G Schulze^{153,169,231,232,233}, Laura J Scott¹⁴⁸, Alessandro Serretti²³⁴, Giuseppe Fanelli^{234, 235}, Jianxin Shi²³⁶, Stanley I Shyn²³⁷, Lea Sirignano¹⁶⁹, Pamela Sklar^4,5, Olav B Smeland^20,21, Jordan W Smoller^92,191,238, Edmund J S Sonuga-Barke²³⁹, Gianfranco Spalletta^240,241, John S Strauss^75,189, Beata Świątkowska²⁴², Maciej Trzaskowski¹³, Ming T Tsuang²⁴³, Gustavo Turecki²⁴⁴, Laura Vilar-Ribó^128,131, John B Vincent²⁴⁵, Henry Völzke²⁴⁶, James TR Walters¹⁶⁵, Cynthia Shannon Weickert^14,176, Thomas W Weickert^14,176, Myrna M Weissman^247,248, Leanne M Williams²⁴⁹, Naomi R Wray^13,206, Clement C Zai^{92,189,190,250,251,252}, Esben Agerbo^114,212,253, Anders D Børglum^{100,101,102,103}, Gerome Breen^7,8, Ditte Demontis^{100,101,102,103}, Annette Erlangsen^{103,254,255,256}, Tõnu Esko^257,258, Joel Gelernter^81,82, Stephen J Glatt²⁵⁹, David M Hougaard^253,260, Hai-Gwo Hwu²⁶¹, Po-Hsiu Kuo^54,56, Cathryn M Lewis^8,262, Qingqin S Li²⁶³, Chih-Min Liu⁵⁴, Nicholas G Martin¹², Andrew M McIntosh¹¹, Sarah E Medland¹², Ole Mors^253,264, Merete Nordentoft^253,265, Catherine M Olsen²⁶⁶, David Porteous²⁶⁷, Daniel J Smith²⁶⁸, Eli A Stahl^4,257,269, Murray B Stein²⁷⁰, Danuta Wasserman⁹⁹, Thomas Werge^{126,253,271,272}, David C Whiteman²⁶⁶, Virginia Willour²⁷³, the VA Million Veteran Program (MVP), the MVP Suicide Exemplar Workgroup, Suicide Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Eating Disorder Working Group of the Psychiatric Genomics Consortium, German Borderline Genomics Consortium, Hilary Coon^1,2,274, Jean C Beckham^275,276, Nathan A Kimbrel^275,276, Douglas M Ruderfer^9,277,278.

¹ Huntsman Mental Health Institute, Salt Lake City, UT, USA

² University of Utah School of Medicine, Department of Psychiatry, Salt Lake City, UT, USA

³ Virginia Commonwealth University, Department of Psychiatry, Richmond, VA, USA

⁴ Icahn School of Medicine at Mount Sinai, Department of Genetics and Genomic Sciences, New York, NY, USA

⁵ Icahn School of Medicine at Mount Sinai, Department of Psychiatry, New York, NY, USA

⁶ Duke University Medical Center, Duke Molecular Physiology Institute, Durham, NC, USA

⁷ King’s College London, National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust, London, UK

⁸ King’s College London, Social Genetic and Developmental Psychiatry Centre, London, UK

⁹ Vanderbilt University Medical Center, Division of Genetic Medicine, Department of Medicine, Vanderbilt Genetics Institute, Nashville, TN, USA

¹⁰ Yale University School of Medicine, Department of Psychiatry, New Haven, CT, USA

¹¹ University of Edinburgh, Division of Psychiatry, Edinburgh, UK

¹² QIMR Berghofer Medical Research Institute, Mental Health and Neuroscience Research Program, Brisbane, QLD, Australia

¹³ The University of Queensland, Institute for Molecular Bioscience, Brisbane, QLD, Australia

¹⁴ Neuroscience Research Australia, Sydney, NSW, Australia

¹⁵ University of New South Wales, School of Medical Sciences, Sydney, NSW, Australia

¹⁶ University of Pennsylvania Perelman School of Medicine, Department of Psychiatry, Philadelphia, PA, USA

¹⁷ Crescenz VAMC, VISN 4 MIRECC, Philadelphia, PA, USA

¹⁸ The University of Queensland, School of Biomedical Sciences, Faculty of Medicine, Brisbane, QLD, Australia

¹⁹ University of Texas Health Science Center, Department of Psychiatry and Behavioral Sciences, Houston, TX, USA

²⁰ Oslo University Hospital, Division of Mental Health and Addiction, Oslo, Norway

²¹ University of Oslo, NORMENT, Oslo, Norway

²² Karolinska Institutet, Department of Medical Epidemiology and Biostatistics, Stockholm, Sweden

²³ University of North Carolina at Chapel Hill, Department of Nutrition, Chapel Hill, NC, USA

²⁴ University of North Carolina at Chapel Hill, Department of Psychiatry, Chapel Hill, NC, USA

²⁵ Indiana University, Department of Medical & Molecular Genetics, Indianapolis, IN, USA

²⁶ Indiana University School of Medicine, Biochemistry and Molecular Biology, Indianapolis, IN, USA

²⁷ Harvard Medical School, Department of Health Care Policy, Boston, MA, USA

²⁸ Columbia University, Departments of Psychiatry and Radiology, New York, NY, USA

²⁹ Indiana University School of Medicine, Departments of Psychiatry and Medical and Molecular Genetics, Indianapolis, IN, USA

³⁰ Lausanne University Hospital and University of Lausanne, Department of Psychiatry, Lausanne, Vaud, Switzerland

³¹ Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Department of Genetic Epidemiology in Psychiatry, Mannheim, Germany

³² Uniformed Services University of the Health Sciences, Department of Psychiatry, Bethesda, MD, USA

³³ Duke University Medical Center, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA

³⁴ Duke University Medical Center, Durham, NC, USA

³⁵ Durham Veterans Affairs Health Care System, Durham, NC, USA

³⁶ Miami VA Health Care System, Miami, FL, USA

³⁷ Durham Veterans Affairs Health Care System, Cooperative Studies Program Epidemiology Center, Durham, NC, USA

³⁸ Boston VA Health Care System, Boston, MA, USA

³⁹ Oak Ridge National Laboratory, Oak Ridge, TN, USA

⁴⁰ Durham Veterans Affairs Health Care System, VA Health Services Research and Development Center of Innovation to Accelerate Discovery and Practice Transformation, Durham, NC, USA

⁴¹ Argonne National Laboratory, University of Chicago Consortium for Advanced Science and Engineering, Chicago, IL, USA

⁴² Los Alamos National Laboratory, Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM, USA

⁴³ Corporal Michael J. Crescenz VA Medical Center, VISN 4 Mental Illness Research, Education, and Clinical Center, Philadelphia, PA, USA

⁴⁴ Perelman School of Medicine, University of Pennsylvania, Department of Psychiatry, Philadelphia, PA, USA

⁴⁵ VA Palo Alto Health Care System, VA Program Evaluation and Resource Center, Palo Alto, CA, USA

⁴⁶ Charité - Universitätsmedizin Berlin, Department of Psychiatry and Psychotherapy, Berlin, Germany

⁴⁷ BioRealm, LLC, Walnut, CA, USA

⁴⁸ Oregon Research Institute, Eugene, OR, USA

⁴⁹ Perelman School of Medicine at the University of Pennsylvania, Department of Psychiatry, Center for Neurobiology and Behavior, Philadelphia, PA, USA

⁵⁰ Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Department of Psychosomatic Medicine and Psychotherapy, Mannheim, Germany

⁵¹ ERCPathlight, Baltimore, MD, USA

⁵² University of Maryland St. Joseph Medical Center, Baltimore, MD, USA

⁵³ Children’s Hospital of Philadelphia, Center for Applied Genomics, Philadelphia, PA, USA

⁵⁴ National Taiwan University Hospital, Department of Psychiatry, Taipei, Taiwan

⁵⁵ National Health Research Institutes, Center for Neuropsychiatric Research, Miaoli County, Taiwan

⁵⁶ National Taiwan University, Institute of Epidemiology and Preventive Medicine, College of Public Health, Taipei, Taiwan

⁵⁷ Utah Department of Health and Human Services, Utah Office of the Medical Examiner, Taylorsville, UT, USA

⁵⁸ University of Utah, Department of Pathology, Salt Lake City, UT, USA

⁵⁹ University of Minnesota, Department of Psychiatry, Minneapolis, MN, USA

⁶⁰ GHU Paris Psychiatrie et Neurosciences, Hôpital Sainte Anne, Paris, France

⁶¹ Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Paris, France

⁶² University Hospital Bellvitge-IDIBELL and CIBEROBN, Department of Psychiatry, Barcelona, Spain

⁶³ Ludwig-Maximilians-University (LMU), Department of Psychiatry and Psychotherapy, Munich, Germany

⁶⁴ Schön Klinik Roseneck affiliated with the Medical Faculty of the University of Munich (LMU), Munich, Germany

⁶⁵ Department of Psychiatry, University of Ibadan, Ibadan, Nigeria.

⁶⁶ Columbia University, Department of Psychiatry, New York, NY, USA

⁶⁷ University of Toronto, Department of Surgery, Faculty of Medicine, Toronto, Canada

⁶⁸ University of California, Los Angeles, Department of Psychiatry and Biobehavioral Science, Semel Institute, David Geffen School of Medicine, Los Angeles, CA, USA

⁶⁹ University of Pennsylvania, The Perelman School of Medicine, Philadelphia, PA, USA

⁷⁰ Weill Cornell Medical College, Department of Psychiatry, New York, NY, USA

⁷¹ Yokohama City University Graduate School of Medicine, Department of Psychiatry, Yokohama, Japan

⁷² University of California San Diego, Biostatistics Research Center, Herbert Wertheim School of Public Health and Human Longevity Science, La Jolla, CA, USA

⁷³ Univ Paris-Est-Créteil, INSERM, IMRB, Translational Neuropsychiatry, Fondation FondaMental, Créteil, France

⁷⁴ Eating Recovery Center, Denver, CO, USA

⁷⁵ Centre for Addiction and Mental Health, Toronto, ON, Canada

⁷⁶ University of Toronto, Department of Psychiatry, Toronto, Canada

⁷⁷ University of Toronto, Institute of Medical Science, Toronto, Canada

⁷⁸ University of California San Diego, Department of Psychiatry, San Diego, CA, USA

⁷⁹ Florida State University, Department of Psychology, Tallahassee, FL, USA

⁸⁰ Michigan State University, Department of Psychology, Lansing, MI, USA

⁸¹ Veterans Affairs Connecticut Healthcare Center, Department of Psychiatry, West Haven, CT, USA

⁸² Yale University School of Medicine, Division of Human Genetics, Department of Psychiatry, New Haven, CT, USA

⁸³ University Medical Center, Department of Psychiatry and Psychotherapy, Mainz, Germany

⁸⁴ The Chicago School of Professional Psychology, Washington DC, Department of Clinical Psychology, Washington, DC, USA

⁸⁵ Emory University School of Medicine, Department of Psychiatry and Behavioral Sciences, Atlanta, GA, USA

⁸⁶ King Abdullah University of Science and Technology, BESE Division, Thuwal, Saudi Arabia

⁸⁷ University of Lausanne-University Hospital of Lausanne (UNIL-CHUV), Department of Psychiatry, Lausanne, Switzerland

⁸⁸ The Hospital for Sick Children, Department of Paediatric Laboratory Medicine, Toronto, Canada

⁸⁹ University of North Dakota School of Medicine and Health Sciences, Department of Psychiatry and Behavioral Science, Fargo, ND, USA

⁹⁰ HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA

⁹¹ Kobe University Graduate School of Medicine, Department of Psychiatry, Kobe, Japan

⁹² Broad Institute, Stanley Center for Psychiatric Research, Cambridge, MA, USA

⁹³ Massachusetts General Hospital, Analytical and Translational Genetics Unit, Boston, MA, USA

⁹⁴ Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, Campus Benjamin Franklin, Department of Psychiatry, Berlin, Germany

⁹⁵ Saint-Petersburg State University, Department of Psychology, Saint-Petersburg, Russian Federation

⁹⁶ V.M. Bekhterev National Medical Research Center for Psychiatry and Neurology, Department of Borderline Disorders and Psychotherapy, Saint-Petersburg, Russian Federation

⁹⁷ The Hospital for Sick Children, Department of Genetics and Genomic Biology, Toronto, Canada

⁹⁸ University of Toronto, McLaughlin Center, Toronto, Canada

⁹⁹ Karolinska Institutet, National Centre for Suicide Research and Prevention of Mental Ill-Health (NASP), LIME, Stockholm, Sweden

¹⁰⁰ Aarhus University, Centre for Genomics and Personalized Medicine, CGPM, Aarhus, Denmark

¹⁰¹ Aarhus University, Centre for Integrative Sequencing, iSEQ, Aarhus, Denmark

¹⁰² Aarhus University, Department of Biomedicine, Aarhus, Denmark

¹⁰³ Aarhus University, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark

¹⁰⁴ University of California Los Angeles, David Geffen School of Medicine, Los Angeles, LA, USA

¹⁰⁵ University of California Los Angeles, Department of Psychiatry and Biobehavioral Science, Semel Institute for Neuroscience and Human Behavior, Los Angeles, LA, USA

¹⁰⁶ King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, London, UK

¹⁰⁷ King’s College London and South London and Maudsley National Health Service Foundation Trust, National Institute for Health Research Biomedical Research Centre, London, UK

¹⁰⁸ University of Michigan, Population Studies Center, Institute for Social Research, Ann Arbor, MI, USA

¹⁰⁹ University of Michigan, Survery Research Center, Institute for Social Research, Ann Arbor, MI, USA

¹¹⁰ Curtin University, School of Psychology, Perth, Western Australia, Australia

¹¹¹ The University of Western Australia, Division of Paediatrics, Perth, Western Australia, Australia

¹¹² University Health Network, Centre for Mental Health, Toronto, Canada

¹¹³ University Health Network, Program for Eating Disorders, Toronto, Canada

¹¹⁴ Aarhus University, National Centre for Register-Based Research, Aarhus, Denmark

¹¹⁵ University of North Carolina at Chapel Hill, Department of Genetics, Chapel Hill, NC, USA

¹¹⁶ Umeå University Medical Faculty, Department of Clinical Sciences, Psychiatry, Umeå, Sweden

¹¹⁷ Diakonhjemmet Hospital, Department of Psychiatric Research, Oslo, Norway

¹¹⁸ Karolinska Institutet, Department of Clinical Neuroscience, Centre for Psychiatry Research, Stockholm, Sweden

¹¹⁹ University of Oslo, NORMENT, Institute of Clinical Medicine, Oslo, Norway

¹²⁰ University of Adelaide, Discipline of Psychiatry, Adelaide, SA, Australia

¹²¹ Dalhousie University, Department of Psychiatry, Halifax, NS, Canada

¹²² National Institute of Mental Health, Klecany, CZ

¹²³ Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden

¹²⁴ Karolinska Institutet, Inst of Environmental Medicine, Stockholm, Sweden

¹²⁵ Berkshire Healthcare NHS Foundation Trust, Psychiatry, Bracknell, UK

¹²⁶ Copenhagen University Hospital, Institute of Biological Psychiatry, Copenhagen Mental Health Services, Copenhagen, Denmark

¹²⁷ iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Copenhagen, Denmark

¹²⁸ Hospital Universitari Vall d’Hebron, Department of Psychiatry, Barcelona, Spain

¹²⁹ Instituto de Salud Carlos III, Biomedical Network Research Centre on Mental Health (CIBERSAM), Madrid, Spain

¹³⁰ University of Barcelona, Department of Genetics, Microbiology & Statistics, Barcelona, Spain

¹³¹ Vall d’Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Psychiatric Genetics Unit, Group of Psychiatry, Mental Health and Addiction, Barcelona, Spain

¹³² University Medicine Greifswald, Department of Psychiatry and Psychotherapy, Greifswald, Mecklenburg-Vorpommern, Germany

¹³³ German Centre for Neurodegenerative Diseases (DZNE), Partner Site Rostock/Greifswald, Greifswald, Mecklenburg-Vorpommern, Germany

¹³⁴ University of Coimbra, Department of Psychiatry, Coimbra, Portugal

¹³⁵ University College London, Division of Psychiatry, London, UK

¹³⁶ Hospital de Clínicas de Porto Alegre, Laboratory of Developmental Psychiatry, Porto Alegre, RS, Brazil

¹³⁷ Universidade Federal do Rio Grande do Sul, Department of Genetics, Porto Alegre, RS, Brazil

¹³⁸ University of Melbourne, Department of Psychiatry, Melbourne Medical School, Melbourne, Australia

¹³⁹ University of Münster, Department of Psychiatry, Münster, Germany

¹⁴⁰ Assistance Publique - Hôpitaux de Paris, Department of Psychiatry and Addiction Medicine, Paris, France

¹⁴¹ FondaMental Foundation, Paris Bipolar and TRD Expert Centres, Paris, France

¹⁴² INSERM, UMR-S1144 Team 1: Biomarkers of relapse and therapeutic response in addiction and mood disorders, Paris, France

¹⁴³ Université Paris Cité, Psychiatry, Paris, France

¹⁴⁴ University of Münster, Institute of Epidemiology and Social Medicine, Münster, Nordrhein-Westfalen, Germany

¹⁴⁵ Mayo Clinic, Health Sciences Research, Rochester, MN, USA

¹⁴⁶ State University of New York Downstate Medical Center, Department of Psychiatry and Behavioral Sciences, New York, NY, USA

¹⁴⁷ Max Planck Institute of Psychiatry, Department of Translational Research in Psychiatry, Munich, Germany

¹⁴⁸ University of Michigan, Center for Statistical Genetics and Department of Biostatistics, Ann Arbor, MI, USA

¹⁴⁹ UMC Utrecht Brain Center, Psychiatry, Utrecht, Netherlands

¹⁵⁰ Universitat Autònoma de Barcelona, Department of Psychiatry and Legal Medicine, Barcelona, Spain

¹⁵¹ University of California San Diego, Department of Psychiatry, La Jolla, CA, USA

¹⁵² University of New South Wales, School of Psychology, Sydney, NSW, Australia

¹⁵³ University Hospital, LMU Munich, Institute of Psychiatric Phenomics and Genomics (IPPG), Munich, Germany

¹⁵⁴ The University of Queensland, Child Health Research Centre, Brisbane, QLD, Australia

¹⁵⁵ UMC Utrecht Hersencentrum Rudolf Magnus, Department of Psychiatry, Utrecht, Netherlands

¹⁵⁶ University of Granada, Mental Health Unit, Department of Psychiatry, Faculty of Medicine, Granada University Hospital Complex, Granada, Spain

¹⁵⁷ CNRS GDR 3557, Institut de Psychiatrie, Paris, France

¹⁵⁸ GHU Paris Psychiatrie et Neurosciences, Department of Evaluation, Prevention and Therapeutic innovation, Paris, France

¹⁵⁹ Université de Paris, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team Pathophysiology of psychiatric diseases, Paris, France

¹⁶⁰ Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1), Jülich, Germany

¹⁶¹ University Hospital Basel, Institute of Medical Genetics and Pathology, Basel, Switzerland

¹⁶² University of Basel, Department of Biomedicine, Basel, Switzerland

¹⁶³ University of Bonn, School of Medicine & University Hospital Bonn, Institute of Human Genetics, Bonn, Germany

¹⁶⁴ Trinity College Dublin, Neuropsychiatric Genetics Research Group, Dept of Psychiatry and Trinity Translational Medicine Institute, Dublin, Ireland

¹⁶⁵ Cardiff University, Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff, UK

¹⁶⁶ University of Southern California, Department of Translational Genomics, Pasadena, CA, USA

¹⁶⁷ Oslo University Hospital, Department of Medical Genetics, Oslo, Norway

¹⁶⁸ University of Bergen, NORMENT, Department of Clinical Science, Bergen, Norway¹⁶⁹ Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Department of Genetic Epidemiology in Psychiatry, Mannheim, Germany

¹⁷⁰ University of Marburg, Centre for Human Genetics, Marburg, Germany

¹⁷¹ Mayo Clinic, Department of Psychiatry & Psychology, Rochester, MN, USA

¹⁷² NorthShore University HealthSystem, Department of Psychiatry and Behavioral Sciences, Evanston, IL, USA

¹⁷³ University of Chicago, Department of Psychiatry and Behavioral Neuroscience, Chicago, IL, USA

¹⁷⁴ Comprehensive Center for Clinical Neurosciences and Mental Health (C3NMH), Medical University of Vienna, Austria.

¹⁷⁵ Medical University of Vienna, Department of Psychiatry and Psychotherapy, Vienna, Austria.

¹⁷⁶ University of New South Wales, School of Psychiatry, Sydney, NSW, Australia

¹⁷⁷ Hospital de Clínicas de Porto Alegre, ADHD Outpatient Program, Adult Division, Porto Alegre, RS, Brazil

¹⁷⁸ Universidade Federal do Rio Grande do Sul, Department of Psychiatry, Porto Alegre, RS, Brazil

¹⁷⁹ Alexandru Obregia Clinical Psychiatric Hospital, Biometric Psychiatric Genetics Research Unit, Bucharest, Romania

¹⁸⁰ University of Granada, Department of Psychiatry, Faculty of Medicine and Biomedical Research Centre (CIBM), Granada, Spain

¹⁸¹ University Regional Hospital. Biomedicine Institute (IBIMA), Mental Health Department, Málaga, Spain

¹⁸² Kaiser Permanente Northern California, Psychiatry, San Francisco, CA, USA

¹⁸³ Poznan University of Medical Sciences, Psychiatric Genetics, Department of Psychiatry, Poznan, Poland

¹⁸⁴ Max Planck Institute of Psychiatry, Munich, Germany

¹⁸⁵ University of Worcester, Department of Psychological Medicine, Worcester, UK

¹⁸⁶ University of Gothenburg, Department of Psychiatry and Neuroscience, Gothenburg, Sweden

¹⁸⁷ UMC Utrecht Brain Center Rudolf Magnus, Psychiatry, Utrecht, Netherlands

¹⁸⁸ University of California San Diego, Institute for Genomic Medicine, La Jolla, CA, USA

¹⁸⁹ University of Toronto, Department of Psychiatry, Toronto, ON, Canada

¹⁹⁰ Harvard TH Chan School of Public Health, Department of Epidemiology, Boston, MA, USA

¹⁹¹ Massachusetts General Hospital, Department of Psychiatry, Boston, MA, USA

¹⁹² Center for Research in Environmental Epidemiology (CREAL), Barcelona, Spain

¹⁹³ University of Gothenburg, Institute of Neuroscience and Physiology, Gothenburg, Sweden

¹⁹⁴ North East London NHS Foundation Trust, Psychiatry, Ilford, UK

¹⁹⁵ Univ Paris Est Créteil, INSERM, AP-HP, IMRB, Translational Neuropsychiatry, DMU IMPACT, FHU ADAPT, Fondation FondaMental, Créteil, France

¹⁹⁶ INSERM, Paris, France

¹⁹⁷ Université Paris Est, Faculté de Médecine, Créteil, France

¹⁹⁸ Massachusetts General Hospital, Psychiatric and Neurodevelopmental Genetics Unit, Boston, MA, USA

¹⁹⁹ Stanford University, Psychiatry & Behavioral Sciences, Stanford, CA, USA

²⁰⁰ Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, MA, USA

²⁰¹ Massachusetts General Hospital, Analytical and Translational Genetics Unit, Cambridge, MA, USA

²⁰² M. Sklodowska-Curie Cancer Center and Institute of Oncology, Cancer Epidemiology and Prevention, Warsaw, Poland

²⁰³ Lindner Center of HOPE, Research Institute, Mason, OH, USA

²⁰⁴ Columbia University College of Physicians and Surgeons, Psychiatry, New York, NY, USA

²⁰⁵ Queensland University of Technology, School of Psychology and Counseling, Brisbane, QLD, Australia

²⁰⁶ The University of Queensland, Queensland Brain Institute, Brisbane, QLD, Australia

²⁰⁷ University of Oslo, Institute of Clinical Medicine, Division of Mental Health and Addiction, Oslo, Norway

²⁰⁸ Amsterdam UMC, Vrije Universiteit and GGZ inGeest, Department of Psychiatry, Amsterdam, Netherlands

²⁰⁹ University of Granada, Department of Nursing, Faculty of Health Sciences and Biomedical Research Centre (CIBM), Granada, Spain

²¹⁰ Norwegian University of Science and Technology - NTNU, Mental Health, Faculty of Medicine and Health Sciences, Trondheim, Norway

²¹¹ St Olavs University Hospital, Psychiatry, Trondheim, Norway

²¹² Aarhus University, Centre for Integrated Register-based Research, Aarhus, Denmark

²¹³ Munich Cluster for Systems Neurology (SyNergy), Munich, Germany

²¹⁴ University of Liverpool, Liverpool, UK

²¹⁵ University of Pittsburgh, Psychiatry and Human Genetics, Pittsburgh, PA, USA

²¹⁶ Erasmus University Medical Center, Psychiatry, Rotterdam, Netherlands

²¹⁷ Rutgers University, RWJMS, NJMS, UBHC, Pisctatway, NJ, USA

²¹⁸ Rutgers University, RWJMS, NJMS, Pisctatway, NJ, USA

²¹⁹ Amsterdam UMC, Vrije Universiteit, Department of Psychiatry and Amsterdam Neuroscience, Amsterdam, Netherlands

²²⁰ Johns Hopkins University School of Medicine, Psychiatry, Baltimore, MD, USA

²²¹ BioMarin Pharmaceuticals, Genetics, London, UK

²²² University of Oxford, St Edmund Hall, Oxford, UK

²²³ University of Oxford, Department of Psychiatry, Oxford, UK

²²⁴ University Hospital Frankfurt, Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, Frankfurt, Germany

²²⁵ Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Department of Genetic Epidemiology in Psychiatry, Mannheim, Baden-Württemberg, Germany

²²⁶ University of Granada, Department of Biochemistry and Molecular Biology II and Institute of Neurosciences, Biomedical Research Centre (CIBM), Granada, Spain

²²⁷ Harvard TH Chan School of Public Health, Department of Environmental Health, Boston, MA, USA

²²⁸ McGill University, Faculty of Medicine, Department of Neurology and Neurosurgery, Montreal, QC, Canada

²²⁹ Montreal Neurological Institute and Hospital, Montreal, QC, Canada

²³⁰ Instituto de Ciencias Biomedicas Universidade de Sao Paulo, Department of Physiology and Biophysics, São Paulo, SP, Brazil

²³¹ Johns Hopkins University School of Medicine, Department of Psychiatry and Behavioral Sciences, Baltimore, MD, USA

²³² National Institute of Mental Health, Human Genetics Branch, Intramural Research Program, Bethesda, MD, USA

²³³ University Medical Center Göttingen, Department of Psychiatry and Psychotherapy, Göttingen, Germany

²³⁴ University of Bologna, Department of Biomedical and Neuro-Motor Sciences, Bologna, Italy

²³⁵ Department of Human Genetics and Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands.

²³⁶ National Cancer Institute, Division of Cancer Epidemiology and Genetics, Bethesda, MD, USA.

²³⁷ Kaiser Permanente Washington, Behavioral Health Services, Seattle, WA, USA

²³⁸ Massachusetts General Hospital, Psychiatric and Neurodevelopmental Genetics Unit (PNGU), Boston, MA, USA

²³⁹ King’s College London, Institute of Psychology, Psychiatry & Neuroscience, London, UK

²⁴⁰ Baylor College of Medicine, Houston, Menninger Department of Psychiatry and Behavioral Sciences, Houston, TX, USA

²⁴¹ IRCCS Santa Lucia Foundation, Rome, Laboratory of Neuropsychiatry, Rome, Italy

²⁴² Nofer Institute of Occupational Medicine, Department of Environmental Epidemiology, Lodz, Poland

²⁴³ University of California, San Diego, Center for Behavioral Genomics, Department of Psychiatry, La Jolla, CA, USA

²⁴⁴ McGill University, Department of Psychiatry, Montreal, QC, Canada

²⁴⁵ Centre for Addiction and Mental Health, Molecular Brain Science, Toronto, ON, Canada

²⁴⁶ University Medicine Greifswald, Institute for Community Medicine, Greifswald, Mecklenburg-Vorpommern, Germany

²⁴⁷ Columbia University College of Physicians and Surgeons, New York, NY, USA

²⁴⁸ New York State Psychiatric Institute, Division of Translational Epidemiology, New York, NY, USA

²⁴⁹ Stanford University, Department of Psychiatry and Behavioral Sciences, Stanford, CA, USA

²⁵⁰ University of Toronto, Institute of Medical Science, Toronto, ON, Canada

²⁵¹ Centre for Addiction and Mental Health, Molecular Brain Science, Campbell Family Mental Health Research Institute, Toronto, ON, Canada

²⁵² University of Toronto, Laboratory Medicine and Pathobiology, Toronto, ON, Canada

²⁵³ iPSYCH, The Lundbeck Foundation Initiative for Integrative Psychiatric Research, Aarhus, Denmark

²⁵⁴ Australian National University, Center of Mental Health Research, Canberra, Australia

²⁵⁵ Johns Hopkins Bloomberg School of Public Health, Department of Mental Health, Baltimore, MD, USA

²⁵⁶ Mental Health Centre Copenhagen, Danish Research Institute for Suicide Prevention, Copenhagen, Denmark

²⁵⁷ Broad Institute, Program in Medical and Population Genetics, Cambridge, MA, USA

²⁵⁸ University of Tartu, Estonian Genome Center, Institute of Genomics, Tartu, Estonia

²⁵⁹ SUNY Upstate Medical University, Department of Psychiatry and Behavioral Sciences, Syracuse, NY, USA

²⁶⁰ Statens Serum Institut, Center for Neonatal Screening, Department for Congenital Disorders, Copenhagen, Denmark

²⁶¹ National Taiwan University Hospital and College of Medicine, Department of Psychiatry, Taipei, Taiwan

²⁶² King’s College London, Department of Medical & Molecular Genetics, London, UK

²⁶³ Janssen Research & Development, LLC, Neuroscience, Titusville, NJ, USA

²⁶⁴ Aarhus University Hospital, Risskov, Psychosis Research Unit, Aarhus, Denmark

²⁶⁵ Copenhagen University Hospital, Mental Health Center Copenhagen, Copenhagen, Denmark

²⁶⁶ QIMR Berghofer Medical Research Institute, Department of Population Health, Brisbane, QLD, Australia

²⁶⁷ University of Edinburgh, Institute for Genetics and Molecular Medicine, Edinburgh, UK

²⁶⁸ University of Edinburgh, Centre for Clinical Brain Sciences, Edinburgh, UK

²⁶⁹ Regeneron Genetics Center, Analytical Genetics and Data Science, Tarrytown, NY, USA

²⁷⁰ University of California San Diego, Department of Psychiatry and School of Public Health, La Jolla, CA, USA

²⁷¹ University of Copenhagen, Department of Clinical Medicine, Copenhagen, Denmark

²⁷² University of Copenhagen, Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, Copenhagen, Denmark

²⁷³ University of Iowa, Department of Psychiatry, Iowa City, IA, USA

²⁷⁴ University of Utah School of Medicine, Biomedical Informatics, Salt Lake City, UT, USA

²⁷⁵ Durham Veterans Affairs Health Care System, VISN 6 Mid-Atlantic Mental Illness Research, Education, and Clinical Center, Durham, NC, USA

²⁷⁶ Duke University School of Medicine, Department of Psychiatry and Behavioral Sciences, Durham, NC, USA

²⁷⁷ Vanderbilt University Medical Center, Department of Biomedical Informatics, Nashville, TN, USA

²⁷⁸ Vanderbilt University Medical Center, Department of Psychiatry and Behavioral Sciences, Nashville, TN, USA.

MVP Suicide Exemplar Workgroup consists of the following individuals:

Silvia Crivelli, Ph.D. (Lawrence Berkeley National Laboratory), Michelle F. Dennis, B.A. (Durham Veterans Affairs Health Care System & Duke University School of Medicine), Phillip D. Harvey, Ph.D. (University of Miami Miller School of Medicine, Miami, FL), Bruce W. Carter (VA Medical Center), Jennifer E. Huffman, Ph.D. (Massachusetts Veterans Epidemiology Research and Information Center, VA Boston Healthcare System), Daniel Jacobson, Ph.D. (Oak Ridge National Laboratory), Ravi Madduri, Ph.D. (Argonne National Laboratory), and John Pestian, Ph.D. (Oak Ridge National Laboratory).

VA Million Veteran Program (MVP) consists of the following individuals:

J. Michael Gaziano, M.D., M.P.H. (co-chair, VA Boston Healthcare System), Sumitra Muralidhar, Ph.D. (co-chair, U.S. Department of Veterans Affairs), Rachel Ramoni, D.M.D., Sc.D. (U.S. Department of Veterans Affairs), Jean Beckham, Ph.D. (Durham VA Medical Center), Kyong-Mi Chang, M.D. (Philadelphia VA Medical Center), Christopher J. O’Donnell, M.D., M.P.H. (VA Boston Healthcare System), Philip S. Tsao, Ph.D. (VA Palo Alto Health Care System), James Breeling, M.D. (Ex-Officio, U.S. Department of Veterans Affairs), Grant Huang, Ph.D. (Ex-Officio, U.S. Department of Veterans Affairs), and J.P. Casas Romero, M.D., Ph.D. (Ex-Officio, VA Boston Healthcare System). MVP Program Office: Sumitra Muralidhar, Ph.D., and Jennifer Moser, Ph.D., both of U.S. Department of Veterans Affairs. MVP Recruitment/Enrollment: Recruitment/Enrollment Director/Deputy Director, Boston—Stacey B. Whitbourne, Ph.D., Jessica V. Brewer, M.P.H. (VA Boston Healthcare System). MVP Coordinating Centers: Clinical Epidemiology Research Center (CERC), West Haven—Mihaela Aslan, Ph.D. (West Haven VA Medical Center). Cooperative Studies Program Clinical Research Pharmacy Coordinating Center, Albuquerque—Todd Connor, Pharm.D., Dean P. Argyres, B.S., M.S. (New Mexico VA Health Care System). Genomics Coordinating Center, Palo Alto—Philip S. Tsao, Ph.D. (VA Palo Alto Health Care System). MVP Boston Coordinating Center, Boston—J. Michael Gaziano, M.D., M.P.H. (VA Boston Healthcare System). MVP Information Center, Canandaigua—Brady Stephens, M.S. (Canandaigua VA Medical Center). VA Central Biorepository, Boston—Mary T. Brophy, M.D., M.P.H., Donald E. Humphries, Ph.D., Luis E. Selva, Ph.D. (VA Boston Healthcare System). MVP Informatics, Boston—Nhan Do, M.D., Shahpoor Shayan (VA Boston Healthcare System). MVP Data Operations/Analytics, Boston—Kelly Cho, Ph.D. (VA Boston Healthcare System). MVP Science: Science Operations—Christopher J. O’Donnell, M.D., M.P.H. (VA Boston Healthcare System). Genomics Core— Christopher J. O’Donnell, M.D., M.P.H., Saiju Pyarajan, Ph.D. (VA Boston Healthcare System), Philip S. Tsao, Ph.D. (VA Palo Alto Health Care System). Phenomics Core—Kelly Cho, M.P.H., Ph.D. (VA Boston Healthcare System). Data and Computational Sciences—Saiju Pyarajan, Ph.D. (VA Boston Healthcare System). Statistical Genetics—Elizabeth Hauser, Ph.D. (Durham VA Medical Center). Yan Sun, Ph.D. (Atlanta VA Medical Center). Hongyu Zhao, Ph.D. (West Haven VA Medical Center. Current MVP Local Site Investigators: Peter Wilson, M.D. (Atlanta VA Medical Center); Rachel McArdle, Ph.D. (Bay Pines VA Healthcare System); Louis Dellitalia, M.D. (Birmingham VA Medical Center); Kristin Mattocks, Ph.D., M.P.H. (Central Western Massachusetts Healthcare System); John Harley, M.D., Ph.D. (Cincinnati VA Medical Center); Clement J. Zablocki (VA Medical Center); Jeffrey Whittle, M.D., M.P.H.; Frank Jacono, M.D. (VA Northeast Ohio Healthcare System); Jean Beckham, Ph.D. (Durham VA Medical Center); Edith Nourse Rogers Memorial Veterans Hospital; Salvador Gutierrez, M.D. (Edward Hines, Jr. VA Medical Center); Gretchen Gibson, D.D.S., M.P.H. (Veterans Health Care System of the Ozarks); Kimberly Hammer, Ph.D. (Fargo VA Health Care System); Laurence Kaminsky, Ph.D. (VA Health Care Upstate New York); Gerardo Villareal, M.D. (New Mexico VA Health Care System); Scott Kinlay, M.B.B.S., Ph.D. (VA Boston Healthcare System); Junzhe Xu, M.D. (VA Western New York Healthcare System); Mark Hamner, M.D. (Ralph H. Johnson VA Medical Center); Roy Mathew, M.D. (Columbia VA Health Care System); Sujata Bhushan, M.D. (VA North Texas Health Care System); Pran Iruvanti, DO, Ph.D. (Hampton VA Medical Center); Michael Godschalk, M.D. (Richmond VA Medical Center); Zuhair Ballas, M.D. (Iowa City VA Health Care System); Douglas Ivins, M.D. (Eastern Oklahoma VA Health Care System); Stephen Mastorides, M.D. (James A. Haley Veterans’ Hospital); Jonathan Moorman, M.D., Ph.D. (James H. Quillen VA Medical Center); Saib Gappy, M.D. (John D. Dingell VA Medical Center); Jon Klein, M.D., Ph.D. (Louisville VA Medical Center); Nora Ratcliffe, M.D. (Manchester VA Medical Center); Hermes Florez, M.D., Ph.D. (Miami VA Health Care System); Olaoluwa Okusaga, M.D. (Michael E. DeBakey VA Medical Center); Maureen Murdoch, M.D., M.P.H. (Minneapolis VA Health Care System); Peruvemba Sriram, M.D. (N FL/S GA Veterans Health System); Shing Shing Yeh, Ph.D., M.D. (Northport VA Medical Center); Neeraj Tandon, M.D. (Overton Brooks VA Medical Center); Darshana Jhala, M.D. (Philadelphia VA Medical Center); Samuel Aguayo, M.D. (Phoenix VA Health Care System); David Cohen, M.D. (Portland VA Medical Center); Satish Sharma, M.D. (Providence VA Medical Center); Suthat Liangpunsakul, M.D., M.P.H. (Richard Roudebush VA Medical Center); Kris Ann Oursler, M.D. (Salem VA Medical Center); Mary Whooley, M.D. (San Francisco VA Health Care System); Sunil Ahuja, M.D. (South Texas Veterans Health Care System); Joseph Constans, Ph.D. (Southeast Louisiana Veterans Health Care System); Paul Meyer, M.D., Ph.D. (Southern Arizona VA Health Care System); Jennifer Greco, M.D. (Sioux Falls VA Health Care System); Michael Rauchman, M.D. (St. Louis VA Health Care System); Richard Servatius, Ph.D. (Syracuse VA Medical Center); Melinda Gaddy, Ph.D. (VA Eastern Kansas Health Care System); Agnes Wallbom, M.D., M.S. (VA Greater Los Angeles Health Care System); Timothy Morgan, M.D. (VA Long Beach Healthcare System); Todd Stapley, D.O. (VA Maine Healthcare System); Scott Sherman, M.D., M.P.H. (VA New York Harbor Healthcare System); George Ross, M.D. (VA Pacific Islands Health Care System); Philip Tsao, Ph.D. (VA Palo Alto Health Care System); Patrick Strollo Jr., M.D. (VA Pittsburgh Health Care System); Edward Boyko, M.D. (VA Puget Sound Health Care System); Laurence Meyer, M.D., Ph.D. (VA Salt Lake City Health Care System); Samir Gupta, M.D., M.S.C.S. (VA San Diego Healthcare System); Mostaqul Huq, Pharm.D., Ph.D. (VA Sierra Nevada Health Care System); Joseph Fayad, M.D. (VA Southern Nevada Healthcare System); Adriana Hung, M.D., M.P.H. (VA Tennessee Valley Healthcare System); Jack Lichy, M.D., Ph.D. (Washington, DC VA Medical Center); Robin Hurley, M.D. (W.G., Bill Hefner VA Medical Center); Brooks Robey, M.D. (White River Junction VA Medical Center); and Robert Striker, M.D., Ph.D. (William S. Middleton Memorial Veterans Hospital).