Eating disorders—including anorexia nervosa (AN), bulimia nervosa and binge-eating disorder—are clinically distinct but exhibit symptom overlap and diagnostic crossover. Genomic analyses have mostly examined AN. Here we conducted a genomic meta-analysis of case–control studies of binge-eating behavior (BE; 39,279 cases, 1,227,436 controls), alongside analyses of AN (24,223 cases, 1,243,971 controls) and its subtypes (all European ancestries). We identified six BE-associated loci, including loci associated with a higher body mass index and impulse-control behaviors. AN genome-wide association studies yielded eight loci, validating six loci. Subsequent polygenic risk score analysis demonstrated an association with AN in two East Asian ancestry studies. BE and AN exhibited similar positive genetic correlations with psychiatric disorders but opposing genetic correlations with anthropometric traits. Most of the genetic signal in BE and AN was not shared with body mass index. We have extended eating disorder genomics beyond AN; future work will incorporate multiple diagnoses and global ancestries. This research identified six areas in the genome that are associated with binge eating, and eight areas that are associated with anorexia nervosa, in people of European ancestry. Binge eating has both shared and distinct genetic features compared with anorexia nervosa.

Eating disorders -including anorexia nervosa (AN), bulimia nervosa, and binge eating disorder-are clinically distinct but exhibit symptom overlap and diagnostic crossover. Genomic analyses have mostly examined AN. We conducted the first genomic meta-analysis of binge eating behaviour (BE; 39,279 cases, 1,227,436 controls), alongside new analyses of AN (24,223 cases, 1,243,971 controls) and its subtypes (all European ancestries). We identified six loci associated with BE, including loci associated with higher body mass index (BMI) and impulse-control behaviours. AN GWAS yielded eight loci, validating six loci. Subsequent polygenic risk score analysis demonstrated an association with AN in two East Asian ancestry cohorts. BE and AN exhibited similar positive genetic correlations with psychiatric disorders, but opposing genetic correlations with anthropometric traits. Most of the genetic signal in BE and AN was not shared with BMI. We have extended eating disorder genomics beyond AN; future work will incorporate multiple diagnoses and global ancestries.

Altered reward processing is proposed to be central to the pathology of anorexia nervosa (AN). This study aimed to investigate how aspects of reward dysfunction relate to suicidal thoughts and behaviours (STBs) in AN. We compared responses on self-report measures of general (i.e., anticipatory, consummatory, and social reward) and disorder-specific (i.e., self-starvation reward) reward between individuals with AN with (AN + STBs; n = 28) or without (AN; n = 31) lifetime active STBs and healthy controls (HC; n = 32). Further, we examined whether interactions between general and disorder-specific reward dysfunction were associated with lifetime active STBs in AN. Compared to AN and HC groups, the AN + STBs group reported significantly lower anticipatory and social reward; both AN + STBs and AN groups reported higher self-starvation reward than HCs. When accounting for the effects of depression, group differences became non-significant for general rewards but remained significant for disorder-specific reward processing. The interaction between anticipatory and self-starvation reward was significantly associated with STB risk beyond the effects of depression: AN participants reporting high self-starvation reward were at elevated STB risk regardless of anticipatory reward levels, whereas those with low self-starvation reward showed increased STBs only when anticipatory reward was also low. Our results suggest that the combination of general and disorder-specific reward processes may shape distinct suicidality risk profiles in AN.

Background: Individuals with anorexia nervosa (AN) are hypothesized to experience impairments in flexible, computationally-intensive model-based decision-making and to over-rely on simpler, more automatic strategies, such as model-free decision-making. However, research investigating model-based versus model-free learning disturbances in AN has been mixed and limited by cross-sectional investigations at a single illness stage. Methods: We administered a Markov Two Stage Decision Task capturing model-based and model-free decision-making to AN (n=23), weight-restored AN (WR; n=34), and non-eating disorder control (NC; n=50) participants. Decision-making differences were examined using Reinforcement Learning and One-Trial-Back Stay/Switch models. Regressions examined cross-sectional and longitudinal relations between model-based and model-free estimates and clinical variables. Results: There were no between-group differences across model-based or model-free estimates (ps=.099-.901). However, the WR group showed some indications of model-based deficits (e.g., difficulty distinguishing rare versus common task transitions). Cross-sectionally, higher model-based estimates were associated with lower BMIs (ps=.014-.017), driven by NC participants. There was an interaction between group and One-Trial-Back Stay/Switch model-free estimates on test meal intake (p=.039); higher model-free estimates were associated with greater intake in NC, but lower intake in WR. Longitudinally, there was a significant group by model-based learning estimate interaction on follow-up BMI (ps=.027-.006); higher model-based estimates predicted higher BMIs for WR, but lower BMIs for AN at follow-up. Conclusions: Model-based and model-free decision-making and their relations with clinical variables differed according to stage of illness, as well as cross-sectional or longitudinal measurement, in AN. Greater attention to contextual variables is needed in future computational models examining decision-making in AN.

Objectives/Goals: Children with chronic respiratory technology needs (CRTN) are becoming a dominant patient group in pediatric intensive care units (ICUs). However, little is known about patient-level, long-term outcomes in this population. The lack of such knowledge may lead to inadequate ICU therapies, interventions, or follow-up care. Methods/Study Population: This project will deploy a set of ecological momentary assessment (EMA) modules measuring real-time functioning as well as standardized instruments to measure child and family outcomes including health care utilization, physical functioning, and health-related quality of life following pediatric critical illness in children with CRTN. EMA has particular strength in assessing conditions where individual-level characteristics vary over time, as after critical illness. EMA’s recurrent measurements allow for evaluation of the variables’ temporal course and limit the potential for bias associated with recall surveys. Pulmonary function in children with CRTN in this study will be monitored over time using standardized pulmonary metrics and information from home respiratory machines. Results/Anticipated Results: This work tests the central hypothesis that long-term functional outcomes in children with CRTN are predicted by multimodal data obtained during and shortly after critical illness. To date, 17 families (of a planned 70) have been enrolled. Adherence to EMA modules is high, with 80% completion. Following serial data collection at 3, 6, and 9 months after hospital discharge, phenotypes of recovery (including improvement, stability, or deterioration) will be described. This will include 1) describing the patient demographic and clinical features associated with each long-term outcome trajectory and 2) identifying subgroups with similar outcome trajectories using patient demographics, features of the clinical illness, and EMA data using both traditional biostatistical and causal analysis techniques. Discussion/Significance of Impact: This project will provide important insights into the long-term outcomes following critical illness of children with CRTN while utilizing an innovative methodology. This proposal will provide the necessary information to drive future clinical trials assessing potential interventions at a number of different points to improve outcomes.

OBJECTIVE:To examine the relationship between levels of household food insecurity and disordered eating behaviors (DEB) among youth and young adults with youth-onset type 1 (T1D) and type 2 diabetes (T2D). METHOD:We used cross-sectional data from the multicenter SEARCH for Diabetes in Youth Study (2015-2020). The Household Food Security Survey Module and the Diabetes Eating Problem Survey-Revised (DEPS-R) were utilized to measure household food insecurity and continuous scores for DEB. In each stratum of diabetes type, we evaluated the association of household food insecurity levels with DEB through linear regression adjusting for potential confounders. RESULTS:Participants (n = 2669) were on average 21.5 ± 5.1 years old and had a mean diabetes duration of 11.2 ± 3.3 years; 54.2% were female, 64.0% non-Hispanic white, and respectively 12.9%, 11.1%, and 8.43% experienced marginal, low, and very low food security. The overall unadjusted mean DEPS-R score was 13.5 ± 9.5, with scores of 18.6 ± 11.8 and 21.1 ± 11.7 among T1D and T2D participants with very low food security, and scores of 11.5 ± 8.9 and 15.2 ± 8.8 among T1D and T2D participants with high food security. Compared to participants who reported high food security, adjusted DEPS-R scores among those with very low food security were 5.8 points (95% CI: 4.3, 7.4) and 6.6 points (95% CI: 3.3, 9.2) higher, respectively, in those with T1D (n = 2274) and T2D (n = 395). Less severe levels of household food insecurity showed similar associations with smaller effect sizes. DISCUSSION:Addressing household food insecurity may decrease DEB and future adverse health outcomes for youth and young adults with diabetes.

BACKGROUND AND OBJECTIVES Family-based behavioral treatment (FBT) for children with obesity is provided in weekly parent and child groups over 6 months. A guided self-help FBT program (gshFBT) is provided to the dyad in short meetings. Both interventions provide the same content; however, gshFBT provides this content in less time (FBT = 23 hours, gshFBT = 5.3 hours). This study aimed to evaluate whether gshFBT is noninferior to FBT on child weight loss and cost-effectiveness. METHODS 150 children aged between 7.0 and 12.9 years with a BMI between the 85th and 99.9th percentile and their parent were recruited and randomized to a 6-month program of gshFBT (n = 75) or FBT (n = 75) and were followed 12 months post-treatment. RESULTS A total of 150 children (mean age = 10.1 years, 49% female, mean BMIz = 2.09) and their parent (mean age = 41.5 years, 87% female, 45% Hispanic, 37% White non-Hispanic, 9.7% Asian, 4.8% Black, 7.3% other) were recruited from the San Diego Metropolitan area. Joint LME models showed that gshFBT was noninferior to FBT on child weight loss (ΔBMIz = −0.02 [90% credible interval [CI] −0.08–0.05, P = .65]; ΔBMIp95% = −1.57 [90% CI –4.46–1.31, P = .28]) and cost less (cost/dyad gshFBT = $1498; FBT = $2775). CONCLUSION The gshFBT program provided similar weight losses for children with less contact hours and with lower cost than FBT. The reduced time and ease of scheduling for the family in gshFBT will allow for an increased reach of treatment to a greater proportion of families in need.

OBJECTIVES:Generative Artificial Intelligence (AI) could transform how science is conducted, supporting researchers with writing, coding, peer review, and evidence synthesis. However, it is not yet known how eating disorder researchers utilize generative AI, and uncertainty remains regarding its safe, ethical, and transparent use. The Executive Committee of the International Journal of Eating Disorders disseminated a survey for eating disorder researchers investigating their practices and perspectives on generative AI, with the goal of informing guidelines on appropriate AI use for authors, reviewers, and editors. METHOD:A survey was distributed globally via eating disorder organizations, professional networks, and individual researchers. Researchers (N = 158) of various career stages completed the survey. RESULTS:Nearly three-quarters (70%) reported using generative AI for research, most commonly for proofreading written work or coding support. Nine in 10 took steps to verify AI-generated output, and 1 in 3 disclosed their use of AI. Only 21% reported using AI for peer review, typically in a limited capacity (e.g., proofreading), and always with full human oversight. Authors were comfortable for editors to use AI to support administrative tasks (i.e., selecting reviewers, detecting plagiarism). However, many participants acknowledged key drawbacks of generative AI, including concerns about inaccurate outputs, ethical issues such as plagiarism, the potential for reduced critical thinking, and anticipated negative impacts on the future of eating disorder research. CONCLUSION:These insights informed the development of field-specific guidelines to support authors, reviewers, and editors in the appropriate use of generative AI in eating disorder research and publishing.

Background Epidemiological data offer conflicting views of the natural course of binge-eating disorder (BED), with large retrospective studies suggesting a protracted course and small prospective studies suggesting a briefer duration. We thus examined changes in BED diagnostic status in a prospective, community-based study that was larger and more representative with respect to sex, age of onset, and body mass index (BMI) than prior multi-year prospective studies. Methods Probands and relatives with current DSM-IV BED (n = 156) from a family study of BED ('baseline') were selected for follow-up at 2.5 and 5 years. Probands were required to have BMI > 25 (women) or >27 (men). Diagnostic interviews and questionnaires were administered at all timepoints. Results Of participants with follow-up data (n = 137), 78.1% were female, and 11.7% and 88.3% reported identifying as Black and White, respectively. At baseline, their mean age was 47.2 years, and mean BMI was 36.1. At 2.5 (and 5) years, 61.3% (45.7%), 23.4% (32.6%), and 15.3% (21.7%) of assessed participants exhibited full, sub-threshold, and no BED, respectively. No participants displayed anorexia or bulimia nervosa at follow-up timepoints. Median time to remission (i.e. no BED) exceeded 60 months, and median time to relapse (i.e. sub-threshold or full BED) after remission was 30 months. Two classes of machine learning methods did not consistently outperform random guessing at predicting time to remission from baseline demographic and clinical variables. Conclusions Among community-based adults with higher BMI, BED improves with time, but full remission often takes many years, and relapse is common.

OBJECTIVE:The Interpersonal Theory of Suicide posits that suicidal behavior results from thwarted belongingness, perceived burdensomeness, and capability for suicide. Considering that food insecurity (FI) may be linked to these constructs to differing extents based on severity of FI, this study examined cross-sectional associations between levels of FI and suicidal ideation, plans, and attempts in a nationally representative sample of adults in the United States. METHODS:Data for this study were collected in 2001-2003 from 5,552 participants in the National Comorbidity Survey Replication (Mage=44.8 ± 0.5 years; 53.8% female). Prevalence ratios (PRs) and 95% confidence intervals (CIs) were generated using modified Poisson regression to examine past-year ideation, plans, and attempts with intent of lethality by past-year FI level (assessed with a modified version of the Short Form U.S. Household Food Security Scale). RESULTS:After controlling for sociodemographic covariates, low food security was significantly associated with elevated prevalence of suicidal ideation, plans, and attempts (ideation: PR = 2.21, 95% CI 1.32-3.70; plans: PR = 5.42, 95% CI 2.71-10.83; attempts: PR = 5.35, 95% CI 2.38-12.03). Very low food security (i.e., more severe FI) exhibited stronger associations yet with suicidal ideation, plans, and attempts (ideation: PR = 6.99, 95% CI 4.10-11.92; plans: PR = 17.21, 95% CI 8.41-35.24; attempts: PR = 14.72, 95% CI 4.96-43.69). CONCLUSIONS:Findings indicative of a dose-response relationship between FI and suicidal ideation, plans, and attempts emphasize the need to increase reach of food assistance programs, increase availability of mental health services in food-insecure populations, and routinely screen for FI in mental health practice.

SummaryBackgroundObesity is a heterogeneous disease with variable treatment response. Identification of the unique constellation of contributors to obesity may allow for targeted interventions and improved outcomes.ObjectiveIdentify empirically derived phenotypes of pediatric patients with obesity based on appetitive and psychological correlates of obesity.MethodsThis cross‐sectional study included patients aged 5–12 years who were treated in a weight management clinic and completed standard intake questionnaires including Child Eating Behavior Questionnaire (CEBQ), Vanderbilt ADHD Scale and Pediatric Symptom Checklist. Phenotypes were elicited using latent profile analysis of 12 indicators: eight CEBQ subscales, inattention, hyperactivity/impulsivity, internalizing and externalizing symptoms.ResultsParents/guardians of 384 patients (mean age 9.8 years, mean BMI 30.3 kg/m2) completed the intake questionnaires. A 4‐phenotype model best fits the data. Hedonic Impulsive phenotype (42.5%) exhibited high food enjoyment and hyperactivity/impulsivity. Inattentive Impulsive phenotype (27.4%) exhibited overall low food approach and high food avoid behaviours, and highest inattention. Hedonic Emotional phenotype (20.8%) scored the highest on food enjoyment, internalizing and externalizing symptoms. Picky Eating phenotype (9.3%) scored the lowest on food approach, inattention, hyperactivity/impulsivity, internalizing and externalizing symptoms.ConclusionAppetitive traits and psychological symptoms appear to cluster in distinct patterns, giving rise to four unique phenotypic profiles, which, if replicated, may help inform the development of tailored treatment plans.

OBJECTIVE:Negative urgency (i.e., acting rashly when experiencing negative affect; NU), is a theorised maintenance factor in binge-eating type eating disorders. This study examined the association between trait NU and eating disorder severity, momentary changes in state NU surrounding episodes of binge eating, and the momentary mechanistic link between affect, rash action, and binge-eating risk. METHODS:Participants were 112 individuals with binge-eating disorder (BED). Baseline measures included the UPPS-P Impulsive Behaviour Scale to assess trait NU and the Eating Disorders Examination to assess binge-eating frequency and global eating disorder severity. Ecological momentary assessment captured real-time data on binge eating, negative affect, and state NU. RESULTS:Multiple regression analysis revealed a strong association between trait NU and eating disorder severity. Generalised estimating equations showed that state NU increased before and decreased after binge-eating episodes, and that this pattern was not moderated by trait-level NU. Finally, a multilevel structural equation model indicated that increases in rash action mediated the momentary relationship between states of high negative affect and episodes of binge eating. CONCLUSION:These findings underscore the importance of both trait and state NU in binge-eating type eating disorders, and suggest NU as a potential key target for intervention.

Background Loss of control eating is more likely to occur in the evening and is uniquely associated with distress. No studies have examined the effect of treatment on within-day timing of loss of control eating severity. We examined whether time of day differentially predicted loss of control eating severity at baseline (i.e. pretreatment), end-of-treatment, and 6-month follow-up for individuals with binge-eating disorder (BED), hypothesizing that loss of control eating severity would increase throughout the day pretreatment and that this pattern would be less pronounced following treatment. We explored differential treatment effects of cognitive-behavioral guided self-help (CBTgsh) and Integrative Cognitive-Affective Therapy (ICAT).Methods Individuals with BED (N = 112) were randomized to receive CBTgsh or ICAT and completed a 1-week ecological momentary assessment protocol at baseline, end-of-treatment, and 6-month follow-up to assess loss of control eating severity. We used multilevel models to assess within-day slope trajectories of loss of control eating severity across assessment periods and treatment type.Results Within-day increases in loss of control eating severity were reduced at end-of-treatment and 6-month follow-up relative to baseline. Evening acceleration of loss of control eating severity was greater at 6-month follow-up relative to end-of-treatment. Within-day increases in loss of control severity did not differ between treatments at end-of-treatment; however, evening loss of control severity intensified for individuals who received CBTgsh relative to those who received ICAT at 6-month follow-up.Conclusions Findings suggest that treatment reduces evening-shifted loss of control eating severity, and that this effect may be more durable following ICAT relative to CBTgsh.

Background: Individuals with eating disorders (EDs) often struggle with markedly low self- esteem and are at risk for suicidal behavior. Dissociation and perceived burdensomeness are often cited as facilitators of suicidal outcomes. Specifically, perceived burdensomeness is comprised of self-hate and liability on others, although it remains unclear which variables most heavily influence suicidal behavior in EDs.Methods: In a sample of 204 women with bulimia nervosa, the present study examined the potential impact of self-hate and dissociation on suicidal behavior. We hypothesized that suicidal behavior would be equally, and potentially more strongly, related to self-hate than dissociation. Regression analyses investigated the unique effects of these variables on suicidal behavior.Results: Consistent with our hypothesis, a significant relationship emerged between self-hate and suicidal behavior (B = 0.262, SE = 0.081, p < .001, CIs = 0.035-0.110, R-squared =0.07) but not between dissociation and suicidal behavior (B = 0.010, SE = 0.007, p = .165, CIs = - 0.389-2.26, R-squared =0.010). Additionally, when controlling for one another, both self-hate (B = 0.889, SE = 0.246, p < .001, CIs = 0.403-1.37) and capability for suicide (B = 0.233, SE = 0.080, p = .004, CIs = 0.076-0.391) were uniquely and independently associated with suicidal behavior.Limitations: Future work should include longitudinal analyses to understand temporal relationships among study variables.Conclusions: In sum, when considering suicidal outcomes, these findings support a view that highlights personal loathing rooted in self-hate rather than de-personalizing aspects of dissociation. Accordingly, self-hate may emerge as a particularly valuable target for treatment and suicide prevention in EDs.

OBJECTIVE:To review the recent literature on the proposed entity of "terminal anorexia nervosa."METHOD:Review of recent literature on the concept of "terminal AN" as well as past and supporting work.RESULTS:The cases and proposed definitions are reviewed, as is the growing literature on this topic. Problems exist with predicting outcomes and thus, determining futility, as well as about capacity for decision-making.DISCUSSION:To make decisions about treatment futility, the existing database for predicting AN course and treatment response must expand greatly. In addition, while decisional capacity is central to the debate, its determination may be unusually complex in this situation. The gaps identified point to extensive needs for future research, but they also indicate that the concept of "terminal AN" cannot be defined at present and should not be used.PUBLIC SIGNIFICANCE:Anorexia nervosa is challenging to treat, and it often lasts for years. There is debate about whether palliative care or medical aid in dying should be considered. Identifying who has a terminal case of AN is important for this question, but we have limited ability to predict a given individual's outcome at present, and there are concerns about the ability of those with AN to make treatment decisions. This means the concept of "terminal AN" should not currently be used.

OBJECTIVE:The present study sought to characterize the temporal patterns of binge eating and theorized maintenance factors among individuals with binge-eating disorder (BED).METHOD:Ecological momentary assessment of 112 individuals and mixed-effects models were used to characterize the within- and between-day temporal patterns of eating behaviors (binge eating, loss of control only eating, and overeating only), positive and negative affect, emotion regulation difficulty, and food craving.RESULTS:Risk for binge eating and overeating only was highest around 5:30 p.m., with additional binge-eating peaks around 12:30 and 11:00 p.m. In contrast, loss of control eating without overeating was more likely to occur before 2:00 p.m. Risk for binge eating, loss of control only eating, and overeating only did not vary across days in the week. There was no consistent pattern of change in negative affect throughout the day, but it decreased slightly on the weekend. Positive affect showed a decrease in the evenings and a smaller decrease on the weekend. The within-day patterns of food craving, and to some extent emotion regulation difficulty, resembled the pattern of binge eating, with peaks around meal times and at the end of the night.DISCUSSION:Individuals with BED appear most susceptible to binge-eating around dinner time, with heightened risk also observed around lunch time and late evening, though the effects were generally small. These patterns appear to most strongly mimic fluctuations in craving and emotion dysregulation, although future research is needed to test the temporal relationships between these experiences directly.PUBLIC SIGNIFICANCE:It is unknown which times of the day and days of the week individuals with binge-eating disorder are most at risk for binge eating. By assessing binge-eating behaviors in the natural environment across the week, we found that individuals are most likely to binge in the evening, which corresponds to the times when they experience the strongest food craving and difficulty with regulating emotions.

Overweight and obesity affect 45% of children and increases the risk for several negative health sequelae. Family-Based Behavioral Treatment (FBT) is the most efficacious treatment for child weight management and consists of nutrition and physical activity education, behavior change skills and parenting skills training. FBT is time and staff intensive and can include 20, 60-min separate groups for parents and children, as well as 20-min behavior coaching sessions to help problem solve barriers to implementing the skills learned and individualize the program. Guided self-help (GSH) therapies involve providing families a manual to review independently and brief coaching sessions by an interventionist to facilitate adherence. We developed a GSH version of FBT (gshFBT) which provides a manual to both parents and children and includes 14, 20-min coaching sessions over 6-months. The current study randomized 150 children (mean age = 10.1 years (SD =1.38); mean BMI% = 97.3% (SD = 2.84); mean BMIz = 2.09 (SD = 0.40); 49% female; 43% Hispanic) and one of their parents (mean age = 41.8 years (SD = 6.52); mean BMI = 32.0 (SD = 7.24); 87.3% female; 43% Hispanic) to either a group-based FBT program or a gshFBT program. Assessments are conducted at baseline, post-treatment (6 months), 6-month follow-up (12 months) and 12-month follow-up (18 months). Primary outcomes are child weight change (BMIz) and cost effectiveness. Recruitment occurred between May 2017 and October 2021 and follow-up assessments are underway. Given the public health concern for children with obesity and the low level of access to FBT, gshFBT could prove extremely useful to provide intervention to a greater proportion of the population.

In this issue of International Journal of Eating Disorders, Walsh et al. review the research to date comparing atypical anorexia nervosa (atypical AN) and AN. Most of the differences observed related to weight; eating disorder and noneating disorder psychopathology and complications were similar. The results could suggest that atypical AN and AN are not really different, and these findings should spur further research. Whether informative weight thresholds exist is a critical question. Beyond, why weight differs in these two groups is of great interest. If the two entities can be separated, does this separation predict longitudinal outcome or response to treatment? The high prevalence of atypical AN in clinical settings emphasizes the urgency of continuing research.

OBJECTIVE:Suicidal behavior is heritable and is a major cause of death worldwide. Two large-scale genome-wide association studies (GWASs) recently discovered and cross-validated genome-wide significant (GWS) loci for suicide attempt (SA). The present study leveraged the genetic cohorts from both studies to conduct the largest GWAS meta-analysis of SA to date. Multi-ancestry and admixture-specific meta-analyses were conducted within groups of significant African, East Asian, and European ancestry admixtures.METHODS:This study comprised 22 cohorts, including 43,871 SA cases and 915,025 ancestry-matched controls. Analytical methods across multi-ancestry and individual ancestry admixtures included inverse variance-weighted fixed-effects meta-analyses, followed by gene, gene-set, tissue-set, and drug-target enrichment, as well as summary-data-based Mendelian randomization with brain expression quantitative trait loci data, phenome-wide genetic correlation, and genetic causal proportion analyses.RESULTS:Multi-ancestry and European ancestry admixture GWAS meta-analyses identified 12 risk loci at p values <5×10-8. These loci were mostly intergenic and implicated DRD2, SLC6A9, FURIN, NLGN1, SOX5, PDE4B, and CACNG2. The multi-ancestry SNP-based heritability estimate of SA was 5.7% on the liability scale (SE=0.003, p=5.7×10-80). Significant brain tissue gene expression and drug set enrichment were observed. There was shared genetic variation of SA with attention deficit hyperactivity disorder, smoking, and risk tolerance after conditioning SA on both major depressive disorder and posttraumatic stress disorder. Genetic causal proportion analyses implicated shared genetic risk for specific health factors.CONCLUSIONS:This multi-ancestry analysis of suicide attempt identified several loci contributing to risk and establishes significant shared genetic covariation with clinical phenotypes. These findings provide insight into genetic factors associated with suicide attempt across ancestry admixture populations, in veteran and civilian populations, and in attempt versus death.