The case for eliminating excessive worry as a requirement for generalized anxiety disorder: a cross-national investigation.

BACKGROUND: Around the world, people living in objectively difficult circumstances who experience symptoms of generalized anxiety disorder (GAD) do not qualify for a diagnosis because their worry is not 'excessive' relative to the context. We carried out the first large-scale, cross-national study to explore the implications of removing this excessiveness requirement. METHODS: Data come from the World Health Organization World Mental Health Survey Initiative. A total of 133 614 adults from 12 surveys in Low- or Middle-Income Countries (LMICs) and 16 surveys in High-Income Countries (HICs) were assessed with the Composite International Diagnostic Interview. Non-excessive worriers meeting all other DSM-5 criteria for GAD were compared to respondents meeting all criteria for GAD, and to respondents without GAD, on clinically-relevant correlates. RESULTS: Removing the excessiveness requirement increases the global lifetime prevalence of GAD from 2.6% to 4.0%, with larger increases in LMICs than HICs. Non-excessive and excessive GAD cases worry about many of the same things, although non-excessive cases worry more about health/welfare of loved ones, and less about personal or non-specific concerns, than excessive cases. Non-excessive cases closely resemble excessive cases in socio-demographic characteristics, family history of GAD, and risk of temporally secondary comorbidity and suicidality. Although non-excessive cases are less severe on average, they report impairment comparable to excessive cases and often seek treatment for GAD symptoms. CONCLUSIONS: Individuals with non-excessive worry who meet all other DSM-5 criteria for GAD are clinically significant cases. Eliminating the excessiveness requirement would lead to a more defensible GAD diagnosis.

Interactive effects of genetic liability and combat exposure on risk of alcohol use disorder among US service members.

BACKGROUND: An improved understanding of pathways to alcohol use disorder (AUD) among service members may inform efforts to reduce the substantial impact of AUD on this population. This study examined whether the relationship between a service-related risk factor (combat exposure) and later AUD varied based on individual differences in genetic liability to AUD. METHODS: The sample consisted of 1203 US Army soldiers of genetically determined European ancestry who provided survey and genomic data in the Army STARRS Pre/Post Deployment Study (PPDS; 2012-2014) and follow-up survey data in wave 1 of the STARRS Longitudinal Study (2016-2018). Logistic regression was used to estimate the conditional effect of combat exposure level (self-reported in PPDS) on odds of probable AUD diagnosis at follow-up, as a function of a soldier's polygenic risk score (PRS) for AUD. RESULTS: The direct effect of combat exposure on AUD risk was non-significant (AOR=1.12, 95 % CI=1.00-1.26, p=.051); however, a significant combat exposure x PRS interaction was observed (AOR=1.60, 95 % CI=1.03-2.46, p=.033). Higher combat exposure was more strongly associated with elevated AUD risk among soldiers with heightened genetic liability to AUD. CONCLUSIONS: The effect of combat exposure on AUD risk appeared to vary based on a service member's level of genetic risk for AUD. Continued investigation is warranted to determine whether PRS can help stratify AUD risk within stress-exposed groups such as combat-deployed soldiers. Such efforts might reveal opportunities to focus prevention efforts on smaller subgroups at the intersection of having both environmental exposures and genetic vulnerability to AUD.

A prediction model for differential resilience to the effects of combat-related stressors in US army soldiers.

OBJECTIVES: To develop a composite score for differential resilience to effects of combat-related stressors (CRS) on persistent DSM-IV post-traumatic stress disorder (PTSD) among US Army combat arms soldiers using survey data collected before deployment. METHODS: A sample of n = 2542 US Army combat arms soldiers completed a survey shortly before deployment to Afghanistan and then again two to three and 8-9 months after redeployment. Retrospective self-reports were obtained about CRS. Precision treatment methods were used to determine whether differential resilience to persistent PTSD in the follow-up surveys could be developed from pre-deployment survey data in a 60% training sample and validated in a 40% test sample. RESULTS: 40.8% of respondents experienced high CRS and 5.4% developed persistent PTSD. Significant test sample heterogeneity was found in resilience (t = 2.1, p = 0.032), with average treatment effect (ATE) of high CRS in the 20% least resilient soldiers of 17.1% (SE = 5.5%) compared to ATE = 3.8% (SE = 1.2%) in the remaining 80%. The most important predictors involved recent and lifetime pre-deployment distress disorders. CONCLUSIONS: A reliable pre-deployment resilience score can be constructed to predict variation in the effects of high CRS on persistent PTSD among combat arms soldiers. Such a score could be used to target preventive interventions to reduce PTSD or other resilience-related outcomes.

Undetected suicide attempts among U.S. soldiers: results from the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS).

BACKGROUND: While previous studies have reported high rates of documented suicide attempts (SAs) in the U.S. Army, the extent to which soldiers make SAs that are not identified in the healthcare system is unknown. Understanding undetected suicidal behavior is important in broadening prevention and intervention efforts. METHODS: Representative survey of U.S. Regular Army enlisted soldiers (n = 24 475). Reported SAs during service were compared with SAs documented in administrative medical records. Logistic regression analyses examined sociodemographic characteristics differentiating soldiers with an undetected SA v. documented SA. Among those with an undetected SA, chi-square tests examined characteristics associated with receiving a mental health diagnosis (MH-Dx) prior to SA. Discrete-time survival analysis estimated risk of undetected SA by time in service. RESULTS: Prevalence of undetected SA (unweighted n = 259) was 1.3%. Annual incidence was 255.6 per 100 000 soldiers, suggesting one in three SAs are undetected. In multivariable analysis, rank ⩾E5 (OR = 3.1[95%CI 1.6-5.7]) was associated with increased odds of undetected v. documented SA. Females were more likely to have a MH-Dx prior to their undetected SA (Rao-Scott χ21 = 6.1, p = .01). Over one-fifth of undetected SAs resulted in at least moderate injury. Risk of undetected SA was greater during the first four years of service. CONCLUSIONS: Findings suggest that substantially more soldiers make SAs than indicated by estimates based on documented attempts. A sizable minority of undetected SAs result in significant injury. Soldiers reporting an undetected SA tend to be higher ranking than those with documented SAs. Undetected SAs require additional approaches to identifying individuals at risk.

Genetics of posttraumatic stress disorder and cardiovascular conditions using Life's Essential 8, Electronic Health Records, and Heart Imaging.

BACKGROUND: Patients with post-traumatic stress disorder (PTSD) experience higher risk of adverse cardiovascular (CV) outcomes. This study explores shared loci, and genes between PTSD and CV conditions from three major domains: CV diagnoses from electronic health records (CV-EHR), cardiac and aortic imaging, and CV health behaviors defined in Life's Essential 8 (LE8). METHODS: We used genome-wide association study (GWAS) of PTSD (N=1,222,882), 246 CV diagnoses based on EHR data from Million Veteran Program (MVP; N=458,061), UK Biobank (UKBB; N=420,531), 82 cardiac and aortic imaging traits (N=26,893), and GWAS of traits defined in the LE8 (N = 282,271 ~ 1,320,016). Shared loci between PTSD and CV conditions were identified using local genetic correlations (rg), and colocalization (shared causal variants). Overlapping genes between PTSD and CV conditions were identified from genetically regulated proteome expression in brain and blood tissues, and subsequently tested to identify functional pathways and gene-drug targets. Epidemiological replication of EHR-CV diagnoses was performed in AllofUS cohort (AoU; N=249,906). RESULTS: Among the 76 PTSD-susceptibility risk loci, 33 loci exhibited local rg with 45 CV-EHR traits (|rg|≥0.4), four loci with eight heart imaging traits(|rg|≥0.5), and 44 loci with LE8 factors (|rg|≥0.36) in MVP. Among significantly correlated loci, we found shared causal variants (colocalization probability > 80%) between PTSD and 17 CV-EHR (in MVP) at 11 loci in MVP, that also replicated in UKBB and/or other cohorts. Of the 17 traits, the observational analysis in the AoU showed PTSD was associated with 13 CV-EHR traits after accounting for socioeconomic factors and depression diagnosis. PTSD colocalized with eight heart imaging traits on 2 loci and with LE8 factors on 31 loci. Leveraging blood and brain proteome expression, we found 33 and 122 genes, respectively, shared between PTSD and CVD. Blood proteome genes were related to neuronal and immune processes, while the brain proteome genes converged on metabolic and calcium-modulating pathways (FDR p <0.05). Drug repurposing analysis highlighted DRD2, NOS1, GFAP, and POR as common targets of psychiatric and CV drugs. CONCLUSION: PTSD-CV comorbidities exhibit shared risk loci, and genes involved in tissue-specific regulatory mechanisms.

Exploring Synaptic Pathways in Traumatic Brain Injury: A Cross-Phenotype Genomics Approach.

Traumatic brain injury (TBI), a global leading cause of mortality and disability, lacks effective treatments to enhance recovery. Synaptic remodeling has been postulated as one mechanism that influences outcomes after TBI. We sought to investigate whether common mechanisms affecting synapse maintenance are shared between TBI and other neuropsychiatric conditions using pathway enrichment tools and genome-wide genotype data, with the goal of highlighting novel treatment targets. We leveraged an integrative approach, combining data from genome-wide association studies with pathway and gene-set enrichment analyses. Literature review-based and Reactome database-driven approaches were combined to identify synapse-related pathways of interest in TBI outcome and to assess for shared associations with conditions in which synapse-related pathobiological mechanisms have been implicated, including Alzheimer's disease, schizophrenia (SCZ), major depressive disorder, post-traumatic stress disorder, attention-deficit hyperactivity disorder, and autism spectrum disorder. Gene and pathway-level enrichment analyses were conducted using MAGMA and its extensions, e- and H-MAGMA, followed by Mendelian randomization to investigate potential causal associations. Of the 98 pathways tested, 32 were significantly enriched in the included conditions. In TBI outcome, we identified significant enrichment in five pathways: "Serotonin clearance from the synaptic cleft" (p = 0.0001), "Presynaptic nicotinic acetylcholine receptors" (p = 0.0003), "Postsynaptic nicotinic acetylcholine receptors" (p = 0.0003), "Highly sodium permeable postsynaptic acetylcholine nicotinic receptors" (p = 0.0001), and "Acetylcholine binding and downstream events" pathways (p = 0.0003). These associations highlight potential involvement of the cholinergic and serotonergic systems in post-TBI recovery. Three of those pathways were shared between TBI and SCZ, suggesting possible pathophysiologic commonalities. In this study, we utilize comparative and integrative genomic approaches across brain conditions that share synaptic mechanisms to explore the pathophysiology of TBI outcomes. Our results implicate associations between TBI outcome and synaptic pathways as well as pathobiological overlap with other neuropsychiatric diseases.

Predicting Suicides Among US Army Soldiers After Leaving Active Service.

Importance: The suicide rate of military servicemembers increases sharply after returning to civilian life. Identifying high-risk servicemembers before they leave service could help target preventive interventions. Objective: To develop a model based on administrative data for regular US Army soldiers that can predict suicides 1 to 120 months after leaving active service. Design, Setting, and Participants: In this prognostic study, a consolidated administrative database was created for all regular US Army soldiers who left service from 2010 through 2019. Machine learning models were trained to predict suicides over the next 1 to 120 months in a random 70% training sample. Validation was implemented in the remaining 30%. Data were analyzed from March 2023 through March 2024. Main outcome and measures: The outcome was suicide in the National Death Index. Predictors came from administrative records available before leaving service on sociodemographics, Army career characteristics, psychopathologic risk factors, indicators of physical health, social networks and supports, and stressors. Results: Of the 800 579 soldiers in the cohort (84.9% male; median [IQR] age at discharge, 26 [23-33] years), 2084 suicides had occurred as of December 31, 2019 (51.6 per 100 000 person-years). A lasso model assuming consistent slopes over time discriminated as well over all but the shortest risk horizons as more complex stacked generalization ensemble machine learning models. Test sample area under the receiver operating characteristic curve ranged from 0.87 (SE = 0.06) for suicides in the first month after leaving service to 0.72 (SE = 0.003) for suicides over 120 months. The 10% of soldiers with highest predicted risk accounted for between 30.7% (SE = 1.8) and 46.6% (SE = 6.6) of all suicides across horizons. Calibration was for the most part better for the lasso model than the super learner model (both estimated over 120-month horizons.) Net benefit of a model-informed prevention strategy was positive compared with intervene-with-all or intervene-with-none strategies over a range of plausible intervention thresholds. Sociodemographics, Army career characteristics, and psychopathologic risk factors were the most important classes of predictors. Conclusions and relevance: These results demonstrated that a model based on administrative variables available at the time of leaving active Army service can predict suicides with meaningful accuracy over the subsequent decade. However, final determination of cost-effectiveness would require information beyond the scope of this report about intervention content, costs, and effects over relevant horizons in relation to the monetary value placed on preventing suicides.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts.

BACKGROUND: Incorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not. METHODS: Elastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts. RESULTS: The eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p=0.006), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD. CONCLUSION: The inclusion of exposure variables adds to the predictive power of MRS. Classification-based MRS may be useful in predicting risk of future PTSD in populations with anticipated trauma exposure. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting PTSD and, relatedly, improve their performance in independent cohorts.

Antecedents, reasons for, and consequences of suicide attempts: Results from a qualitative study of 89 suicide attempts among army soldiers.

Most studies aimed at understanding suicidal behavior have focused on quantifying the associations between putative risk factors and suicidal behavior in comparative studies of cases and controls. The current study, in comparison, exclusively focused on cases-89 Army soldiers presenting for hospital care following a suicide attempt-and attempted to reveal the antecedents of, reasons for, and consequences of suicide attempts. This mixed-methods study using qualitative interviews and self-report surveys/interviews revealed that in most cases, the most recent onset of suicidal thoughts began shortly before the suicide attempt and were not disclosed to others, limiting opportunities for intervention via traditional approaches. The primary reason given for attempting suicide was to escape from psychologically aversive conditions after concluding that no other effective strategies or options were available. Participants reported both negative (e.g., self-view, guilt) and positive (e.g., learning new skills, receiving support) consequences of their suicide attempt-and described things they believe would have prevented them from making the attempt. These findings provide new insights into the motivational and contextual factors for suicidal behavior and highlight several novel directions for prevention and intervention efforts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Distinct trajectories of neuropsychiatric symptoms in the 12 months following traumatic brain injury (TBI): a TRACK-TBI study.

BACKGROUND: Neuropsychiatric symptoms are common after traumatic brain injury (TBI) and often resolve within 3 months post-injury. However, the degree to which individual patients follow this course is unknown. We characterized trajectories of neuropsychiatric symptoms over 12 months post-TBI. We hypothesized that a substantial proportion of individuals would display trajectories distinct from the group-average course, with some exhibiting less favorable courses. METHODS: Participants were level 1 trauma center patients with TBI (n = 1943), orthopedic trauma controls (n = 257), and non-injured friend controls (n = 300). Trajectories of six symptom dimensions (Depression, Anxiety, Fear, Sleep, Physical, and Pain) were identified using growth mixture modeling from 2 weeks to 12 months post-injury. RESULTS: Depression, Anxiety, Fear, and Physical symptoms displayed three trajectories: Stable-Low (86.2-88.6%), Worsening (5.6-10.9%), and Improving (2.6-6.4%). Among symptomatic trajectories (Worsening, Improving), lower-severity TBI was associated with higher prevalence of elevated symptoms at 2 weeks that steadily resolved over 12 months compared to all other groups, whereas higher-severity TBI was associated with higher prevalence of symptoms that gradually worsened from 3-12 months. Sleep and Pain displayed more variable recovery courses, and the most common trajectory entailed an average level of problems that remained stable over time (Stable-Average; 46.7-82.6%). Symptomatic Sleep and Pain trajectories (Stable-Average, Improving) were more common in traumatically injured groups. CONCLUSIONS: Findings illustrate the nature and rates of distinct neuropsychiatric symptom trajectories and their relationship to traumatic injuries. Providers may use these results as a referent for gauging typical v. atypical recovery in the first 12 months post-injury.

Defining Suicidal Thought and Behavior Phenotypes for Genetic Studies.

Background: Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation. Methods: A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394). Results: Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported. Conclusions: Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations.

What I was thinking/what I would do differently: Biological markers and mechanisms of mental health.

At the 39th meeting of the International Society of Traumatic Stress Studies, four leading scientists and clinicians were invited to reflect on their careers, focusing on the biological mechanisms and markers of traumatic stress. Dr. Raul Andero has contributed to understanding how stress alters memory networks in the brain, influencing the development of novel treatments. Dr. Tanja Jovanovic has pioneered the measurement and mechanistic understanding of fear learning, bridging basic and clinical research. Dr. Murray B. Stein has scaled up clinical and lab observations to large populations, refining the field's understanding of traumatic stress. Dr. Arieh Y Shalev has shaped the definition of traumatic stress, pioneering the longitudinal investigation of stress and integrating advanced computational methods to identify individuals at risk. These panelists were asked to reflect on their initial problems, ambitions, concerns, and unexpected challenges, as well as the influence of their work, on new research trajectories. Their insights provide valuable lessons about the process and content of their work, and their pioneering efforts have significantly advanced our understanding of the biological mechanisms and markers of traumatic stress.

A genome-wide investigation into the underlying genetic architecture of personality traits and overlap with psychopathology.

Personality is influenced by both genetic and environmental factors and is associated with other psychiatric traits such as anxiety and depression. The 'big five' personality traits, which include neuroticism, extraversion, agreeableness, conscientiousness and openness, are a widely accepted and influential framework for understanding and describing human personality. Of the big five personality traits, neuroticism has most often been the focus of genetic studies and is linked to various mental illnesses, including depression, anxiety and schizophrenia. Our knowledge of the genetic architecture of the other four personality traits is more limited. Here, utilizing the Million Veteran Program cohort, we conducted a genome-wide association study in individuals of European and African ancestry. Adding other published data, we performed genome-wide association study meta-analysis for each of the five personality traits with sample sizes ranging from 237,390 to 682,688. We identified 208, 14, 3, 2 and 7 independent genome-wide significant loci associated with neuroticism, extraversion, agreeableness, conscientiousness and openness, respectively. These findings represent 62 novel loci for neuroticism, as well as the first genome-wide significant loci discovered for agreeableness. Gene-based association testing revealed 254 genes showing significant association with at least one of the five personality traits. Transcriptome-wide and proteome-wide analysis identified altered expression of genes and proteins such as CRHR1, SLC12A5, MAPT and STX4. Pathway enrichment and drug perturbation analyses identified complex biology underlying human personality traits. We also studied the inter-relationship of personality traits with 1,437 other traits in a phenome-wide genetic correlation analysis, identifying new associations. Mendelian randomization showed positive bidirectional effects between neuroticism and depression and anxiety, while a negative bidirectional effect was observed for agreeableness and these psychiatric traits. This study improves our comprehensive understanding of the genetic architecture underlying personality traits and their relationship to other complex human traits.

Attachment Style, Social Support Network, and Lifetime Suicide Ideation and Suicide Attempts Among New Soldiers in the U.S. Army.

OBJECTIVE: Attachment style and social support networks (SSN) are associated with suicide ideation (SI) and suicide attempt (SA). How these two factors interact is important to understanding the mechanisms of risk for suicidal behaviors and identifying interventions. METHOD: Using the Army Study to Assess Risk and Resilience in Servicemembers New Soldier Study (N = 38,507 soldiers), we examined how three attachment styles (preoccupied, fearful, and secure) and SSN (smaller vs larger) were associated with lifetime SI, SA, and SA among soldiers with SI. The interaction of each attachment style by SSN was examined. RESULTS: All three attachment styles were associated with SI and SA in the total sample (for SA: preoccupied OR = 2.82, fearful OR = 2.84, and secure OR = 0.76). Preoccupied and fearful attachment were associated with SA among suicide ideators. Smaller SSN was associated with a higher risk for all three outcomes (range of ORs = 1.23-1.52). The association of SSN with SI and with SA among suicide ideators was significantly modified by the presence or absence of preoccupied attachment style. Among soldiers without preoccupied attachment, larger SSN was associated with lower risk of SI. Among suicide ideators with preoccupied attachment, a larger SSN was associated with lower risk of SA. CONCLUSION: This study highlights the need for increased understanding of the role of attachment style and social networks in suicide risk, in particular preoccupied attachment among soldiers with SI. A critical next step is to explore these relationships prospectively to guide intervention development.

Genome-wide association study of the common retinal disorder epiretinal membrane: Significant risk loci in each of three American populations.

Epiretinal membrane (ERM) is a common retinal condition characterized by the presence of fibrocellular tissue on the retinal surface, often with visual distortion and loss of visual acuity. We studied European American (EUR), African American (AFR), and Latino (admixed American, AMR) ERM participants in the Million Veteran Program (MVP) for genome-wide association analysis-a total of 38,232 case individuals and 557,988 control individuals. We completed a genome-wide association study (GWAS) in each population separately, and then results were meta-analyzed. Genome-wide significant (GWS) associations were observed in all three populations studied: 31 risk loci in EUR subjects, 3 in AFR, and 2 in AMR, with 48 in trans-ancestry meta-analysis. Many results replicated in the FinnGen sample. Several GWS variants associate to alterations in gene expression in the macula. ERM showed significant genetic correlation to multiple traits. Pathway enrichment analyses implicated collagen and collagen-adjacent mechanisms, among others. This well-powered ERM GWAS identified novel genetic associations that point to biological mechanisms for ERM.

A randomized controlled safety and feasibility trial of floatation-REST in anxious and depressed individuals.

BACKGROUND: Reduced Environmental Stimulation Therapy via floatation (floatation-REST) is a behavioral intervention designed to attenuate exteroceptive sensory input to the nervous system. Prior studies in anxious and depressed individuals demonstrated that single sessions of floatation-REST are safe, well-tolerated, and associated with an acute anxiolytic and antidepressant effect that persists for over 48 hours. However, the feasibility of using floatation-REST as a repeated intervention in anxious and depressed populations has not been well-investigated. METHODS: In this single-blind safety and feasibility trial, 75 individuals with anxiety and depression were randomized to complete six sessions of floatation-REST in different formats: pool-REST (weekly 1-hour float sessions), pool-REST preferred (float sessions with flexibility of duration and frequency), or an active comparator (chair-REST; weekly 1-hour sessions in a Zero Gravity chair). Feasibility (primary outcome) was assessed via an 80% rate of adherence to the assigned intervention; tolerability via study dropout and duration/frequency of REST utilization; and safety via incidence of adverse events and ratings about the effects of REST. RESULTS: Of 1,715 individuals initially screened, 75 participants were ultimately randomized. Six-session adherence was 85% for pool-REST (mean, M = 5.1 sessions; standard deviation, SD = 1.8), 89% for pool-REST preferred (M = 5.3 sessions; SD = 1.6), and 74% for chair-REST (M = 4.4 sessions; SD = 2.5). Dropout rates at the end of the intervention did not differ significantly between the treatment conditions. Mean session durations were 53.0 minutes (SD = 12.3) for pool-REST, 75.4 minutes (SD = 29.4) for pool-REST preferred, and 58.4 minutes (SD = 4.3) for chair-REST. There were no serious adverse events associated with any intervention. Positive experiences were endorsed more commonly than negative ones and were also rated at higher levels of intensity. CONCLUSIONS: Six sessions of floatation-REST appear feasible, well-tolerated, and safe in anxious and depressed individuals. Floatation-REST induces positively-valenced experiences with few negative effects. Larger randomized controlled trials evaluating markers of clinical efficacy are warranted. CLINICAL TRIAL REGISTRATION IDENTIFIER: NCT03899090.

Amplification of positivity for depression and anxiety: Neural prediction of treatment response.

Psychosocial treatments targeting the positive valence system (PVS) in depression and anxiety demonstrate efficacy in enhancing positive affect (PA), but response to treatment varies. We examined whether individual differences in neural activation to positive and negative valence incentive cues underlies differences in benefitting from a PVS-targeted treatment. Individuals with clinically elevated depression and/or anxiety (N = 88, ages 18 to 55) participated in one of two randomized, waitlist-controlled trials of Amplification of Positivity (AMP; NCT02330627, NCT03196544), a cognitive and behavioral intervention targeting the PVS. Participants completed a monetary incentive delay (MID) task during fMRI acquisition at baseline measuring neural activation to the possibility of gaining or losing money. Change in PA from before to after treatment was assessed using the Positive and Negative Affect Schedule. No significant associations were observed between baseline neural activation during gain anticipation and AMP-related changes in PA in regions of interest (striatum and insula) or whole-brain analyses. However, higher baseline striatal and insula activation during loss anticipation was associated with greater increases in PA post-AMP. This study provides preliminary evidence suggesting neural reactivity to negative valence cues may inform who stands to benefit most from treatments targeting the PVS.

Application of an egocentric social network approach to examine changes in social connections following treatment for anxiety and depression: A novel measurement tool for clinical trials research?

The epidemic of loneliness and social isolation has been recognized as a public health crisis warranting the same prioritization as other public health issues today, such as obesity, substance use disorders, and tobacco use. Social disconnection is particularly prevalent and disabling among individuals with anxiety and depression, yet it is inadequately evaluated and addressed in most clinical psychology treatment research. Studies generally employ global measures of perceived connectedness, loneliness, or relationship satisfaction, limiting understanding about elements of one's social network that may change with treatment. This study examined changes in the degree (number of people nominated) and quality of one's social network from pre-to post-treatment using an egocentric social network approach in 59 adults (mean age = 30.8 years, range = 18 to 54) with clinically elevated anxiety or depression who were randomized to a cognitive and behavioral positive valence treatment versus waitlist. Participants (egos) named people in their lives (alters) with whom they discussed important issues or spent free time. For each alter, participants rated how close they felt, how close they thought the alter felt to them, and how frequently they communicated. Linear regressions, which included treatment group as a predictor, revealed no group differences in changes in network degree, perceived alter feelings of closeness, or communication frequency, despite prior findings from this sample indicating larger increases in perceived global connectedness in the treatment group. Unexpectedly, the control group reported a greater increase in perceived closeness to alters. Post-hoc analyses revealed this was explained by the treatment group identifying more distal social ties (e.g., extended family, colleagues, roommates) as alters following treatment - an outcome positively associated with global improvements in connectedness. This proof-of-concept study suggests egocentric social network surveys may provide unique information on treatment-related changes in social functioning. Suggestions are provided for adaptations to facilitate application of social network surveys to mental health treatment research.

Polygenic liability for anxiety in association with comorbid anxiety in multiple sclerosis.

OBJECTIVE: Comorbid anxiety occurs often in MS and is associated with disability progression. Polygenic scores offer a possible means of anxiety risk prediction but often have not been validated outside the original discovery population. We aimed to investigate the association between the Generalized Anxiety Disorder 2-item scale polygenic score with anxiety in MS. METHODS: Using a case-control design, participants from Canadian, UK Biobank, and United States cohorts were grouped into cases (MS/comorbid anxiety) or controls (MS/no anxiety, anxiety/no immune disease or healthy). We used multiple anxiety measures: current symptoms, lifetime interview-diagnosed, and lifetime self-report physician-diagnosed. The polygenic score was computed for current anxiety symptoms using summary statistics from a previous genome-wide association study and was tested using regression. RESULTS: A total of 71,343 individuals of European genetic ancestry were used: Canada (n = 334; 212 MS), UK Biobank (n = 70,431; 1,390 MS), and the USA (n = 578 MS). Meta-analyses identified that in MS, each 1-SD increase in the polygenic score was associated with ~50% increased odds of comorbid moderate anxious symptoms compared to those with less than moderate anxious symptoms (OR: 1.47, 95% CI: 1.09-1.99). We found a similar direction of effects in the other measures. MS had a similar anxiety genetic burden compared to people with anxiety as the index disease. INTERPRETATION: Higher genetic burden for anxiety was associated with significantly increased odds of moderate anxious symptoms in MS of European genetic ancestry which did not differ from those with anxiety and no comorbid immune disease. This study suggests a genetic basis for anxiety in MS.