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Abstract Background The occurrence of post-traumatic stress disorder (PTSD) following a traumatic event is associated with biological differences that can represent the susceptibility to PTSD, the impact of trauma, or the sequelae of PTSD itself. These effects include differences in DNA methylation (DNAm), an important form of epigenetic gene regulation, at multiple CpG loci across the genome. Moreover, these effects can be shared or specific to both central and peripheral tissues. Here, we aim to identify blood DNAm differences associated with PTSD and characterize the underlying biological mechanisms by examining the extent to which they mirror associations across multiple brain regions. Methods As the Psychiatric Genomics Consortium (PGC) PTSD Epigenetics Workgroup, we conducted the largest cross-sectional meta-analysis of epigenome-wide association studies (EWASs) of PTSD to date, involving 5077 participants (2156 PTSD cases and 2921 trauma-exposed controls) from 23 civilian and military studies. PTSD diagnosis assessments were harmonized following the standardized guidelines established by the PGC-PTSD Workgroup. DNAm was assayed from blood using Illumina HumanMethylation450 or MethylationEPIC (850 K) BeadChips. Within each cohort, DNA methylation was regressed on PTSD, sex (if applicable), age, blood cell proportions, and ancestry. An inverse variance-weighted meta-analysis was performed. We conducted replication analyses in tissue from multiple brain regions, neuronal nuclei, and a cellular model of prolonged stress. Results We identified 11 CpG sites associated with PTSD in the overall meta-analysis (1.44e − 09

Abstract Myasthenia gravis (MG) is a rare autoantibody-mediated disease affecting the neuromuscular junction. We performed a genome-wide association study of 5708 MG cases and 432,028 controls of European ancestry and a replication study in 3989 cases and 226,643 controls provided by 23andMe Inc. We identified 12 independent genome-wide significant hits (P

Abstract 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

Abstract 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.

Summary: Background: Post-traumatic stress disorder (PTSD) and depression are common after mild traumatic brain injury (mTBI), but their biological drivers are uncertain. We therefore explored whether polygenic risk scores (PRS) derived for PTSD and major depressive disorder (MDD) are associated with the development of cognate TBI-related phenotypes. Methods: Meta-analyses were conducted using data from two multicenter, prospective observational cohort studies of patients with mTBI: the CENTER-TBI study (ClinicalTrials.gov ID NCT02210221) in Europe (December 2014–December 2017) and the TRACK-TBI study in the US (March 2014–July 2018). In both cohorts, the most common causes of injury were road traffic accidents and falls. Primary outcomes, specifically probable PTSD and depression, were defined at 6 months post-injury using scores ≥33 on the PTSD Checklist-5 and ≥15 on the Patient Health Questionnaire-9, respectively. We calculated PTSD-PRS and MDD-PRS for patients aged ≥17 years who had a Glasgow Coma Scale score of 13–15 upon hospital arrival and assessed their association with PTSD and depression following TBI. We also evaluated the transferability of the findings in a cohort of African Americans. Findings: Overall, 11.8% (219/1869) and 6.7% (124/1869) patients were classified as having probable PTSD and depression, respectively. The PTSD-PRS was significantly associated with higher adjusted odds of PTSD in both cohorts, with a pooled odds ratio (OR) of 1.55 [95% confidence interval (CI) 1.30–1.84, p

Summary: Background: Contemporary surgical practices for traumatic brain injury (TBI) remain unclear. We describe the clinical profile of an 18-centre US TBI cohort with cranial surgery. Methods: The prospective, observational Transforming Research and Clinical Knowledge in Traumatic Brain Injury Study (2014–2018; ClinicalTrials.gov #NCT02119182) enrolled subjects who presented to trauma centre and received head computed tomography within 24-h (h) post-TBI. We performed a secondary data analysis in subjects aged ≥17-years with hospitalisation. Clinical characteristics, surgery type/timing, hospital and six-month outcomes were reported. Findings: Of 2032 subjects (age: mean = 41.4-years, range = 17–89-years; male = 71% female = 29%), 260 underwent cranial surgery, comprising 65% decompressive craniectomy, 23% craniotomy, 12% other surgery. Subjects with surgery (vs. without surgery) presented with worse neurological injury (median Glasgow Coma Scale = 6 vs. 15; midline shift ≥5 mm: 48% vs. 2%; cisternal effacement: 61% vs. 4%; p

Abstract 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.

Objectives: The rate of suicide increased in members of the United States Army since 2011 after the Iraq and Afghanistan wars and continues to be a major concern. In order to reverse this disturbing trend, it is vital to understand the risk and protective factors for suicide death in servicemembers. Methods: Data were obtained from a case-control psychological autopsy study, which compared U.S. Army suicide decedent cases (n = 135) to a probability sample of living controls (n = 255) who are also service members weighted to be representative of the Army. Interviews were conducted with next-of-kin (NOK) and supervisor (SUP) informants. Multivariable logistic regressions models were constructed using predictors significant after controlling for multiple comparisons. Results: The most parsimonious multivariable model controlling for deployment status, as reported by SUP predicting suicide death consisted of four significant variables: a spouse or partner left him or her in the past month (OR = 28.5 [95% CI = 1.8, 442.7] χ² = 5.72, p = .0168); a smaller social network (OR = 4.2 [95% CI = 1.0, 17.3] χ² = 3.97, p = .0462), less likely to seek help from a mental health counselor (OR = 3.4 [95% CI = 1.2, 9.7] χ² = 5.35, p = .0207) and more likely to be described as incautious (OR = 3.8 [95% CI = 1.2, 11.7] χ² = 5.42, p = .0199). The AUC = .88 [95%CI = 0.82, 0.94] for this regression model suggests strong prediction. Conclusions: Our findings suggest that recent relationship problems, especially in soldiers who are less likely to seek out support from others, may be warning signs for detection and prevention of imminent risk of suicide and according to supervisor informant surveys, had neither evidence of a mental health disorder, nor disclosed suicidal ideation or self-harm. Implications for suicide prevention are discussed.

Abstract Observational studies suggest that posttraumatic stress disorder (PTSD) increases risk for various autoimmune diseases. Insights into shared biology and causal relationships between these diseases may inform intervention approaches to PTSD and co-morbid autoimmune conditions. We investigated the shared genetic contributions and causal relationships between PTSD, 18 autoimmune diseases, and 3 immune/inflammatory biomarkers. Univariate MiXeR was used to contrast the genetic architectures of phenotypes. Genetic correlations were estimated using linkage disequilibrium score regression. Bi-directional, two-sample Mendelian randomization (MR) was performed using independent, genome-wide significant single nucleotide polymorphisms; inverse variance weighted and weighted median MR estimates were evaluated. Sensitivity analyses for uncorrelated (MR PRESSO) and correlated horizontal pleiotropy (CAUSE) were also performed. PTSD was considerably more polygenic (10,863 influential variants) than autoimmune diseases (median 255 influential variants). However, PTSD evidenced significant genetic correlation with nine autoimmune diseases and three inflammatory biomarkers. PTSD had putative causal effects on autoimmune thyroid disease (p = 0.00009) and C-reactive protein (CRP) (p = 4.3 × 10−7). Inferences were not substantially altered by sensitivity analyses. Additionally, the PTSD-autoimmune thyroid disease association remained significant in multivariable MR analysis adjusted for genetically predicted inflammatory biomarkers as potential mechanistic pathway variables. No autoimmune disease had a significant causal effect on PTSD (all p values > 0.05). Although causal effect models were supported for associations of PTSD with CRP, shared pleiotropy was adequate to explain a putative causal effect of CRP on PTSD (p = 0.18). In summary, our results suggest a significant genetic overlap between PTSD, autoimmune diseases, and biomarkers of inflammation. PTSD has a putative causal effect on autoimmune thyroid disease, consistent with existing epidemiologic evidence. A previously reported causal effect of CRP on PTSD is potentially confounded by shared genetics. Together, results highlight the nuanced links between PTSD, autoimmune disorders, and associated inflammatory signatures, and suggest the importance of targeting related pathways to protect against disease and disability.

Abstract Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.

Abstract Tinnitus is a heritable, highly prevalent auditory disorder treated by multiple medical specialties. Previous GWAS indicated high genetic correlations between tinnitus and hearing loss, with little indication of differentiating signals. We present a GWAS meta-analysis, triple previous sample sizes, and expand to non-European ancestries. GWAS in 596,905 Million Veteran Program subjects identified 39 tinnitus loci, and identified genes related to neuronal synapses and cochlear structural support. Applying state-of-the-art analytic tools, we confirm a large number of shared variants, but also a distinct genetic architecture of tinnitus, with higher polygenicity and large proportion of variants not shared with hearing difficulty. Tissue-expression analysis for tinnitus infers broad enrichment across most brain tissues, in contrast to hearing difficulty. Finally, tinnitus is not only correlated with hearing loss, but also with a spectrum of psychiatric disorders, providing potential new avenues for treatment. This study establishes tinnitus as a distinct disorder separate from hearing difficulties.

Abstract Sleep duration has been linked to a wide range of negative health outcomes and to reduced life expectancy. We present genome-wide association studies of short ( ≤ 5 h) and long ( ≥ 10 h) sleep duration in adults of European (N = 445,966), African (N = 27,785), East Asian (N = 3141), and admixed-American (N = 16,250) ancestry from UK Biobank and the Million Veteran Programme. In a cross-population meta-analysis, we identify 84 independent loci for short sleep and 1 for long sleep. We estimate SNP-based heritability for both sleep traits in each ancestry based on population derived linkage disequilibrium (LD) scores using cov-LDSC. We identify positive genetic correlation between short and long sleep traits (rg = 0.16 ± 0.04; p = 0.0002), as well as similar patterns of genetic correlation with other psychiatric and cardiometabolic phenotypes. Mendelian randomisation reveals a directional causal relationship between short sleep and depression, and a bidirectional causal relationship between long sleep and depression.

Abstract Background Understanding mental health predictors of imminent suicide attempt (SA; within 30 days) among soldiers with depression and no prior suicide ideation (SI) can inform prevention and treatment. The current study aimed to identify sociodemographic and service-related characteristics and mental disorder predictors associated with imminent SA among U.S. Army soldiers following first documented major depression diagnosis (MDD) with no history of SI. Methods In this case-control study using Army Study to Assess Risk and Resilience in Servicemembers (STARRS) administrative data, we identified 101,046 active-duty Regular Army enlisted soldiers (2010–2016) with medically-documented MDD and no prior SI (MDD/No-SI). We examined risk factors for SA within 30 days of first MDD/No-SI using logistic regression analyses, including socio-demographic/service-related characteristics and psychiatric diagnoses. Results The 101,046 soldiers with documented MDD/No-SI were primarily male (78.0%),

Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Objectives To identify the extent to which the presence of recent stressful events are risk factors for suicide among active‐duty soldiers as reported by informants. Methods Next‐of‐kin (NOK) and supervisors (SUP) of active duty soldiers (n = 135) who died by suicide and two groups of living controls: propensity‐matched (n = 128) and soldiers who reported suicidal ideation in the past year, but did not die (SI) (n = 108) provided data via structured interviews from the Study to Assess Risk and Resilience in Servicemembers (Army STARRS). Multivariate logistic regression analyses were used to create a risk score for suicide. Results The odds of suicide increased significantly for soldiers experiencing relationship problems, military punishment, and perceived failure or humiliation in the month prior to death. Suicide risk models with these risk factors predicted suicide death among those who reported SI in the past year (OR = 5.9, [95% CI = 1.5, 24.0] χ2 = 6.24, p = 0.0125, AUC, 0.73 (0.7, 0.8) NOK) and (OR = 8.6, [95% CI = 1.4, 51.5] χ2 = 5.49, p = 0.0191, AUC, 0.78 (0.7, 0.8); SUP) suggesting the combination of these recent stressors may contribute to the transition from ideation to action. Conclusions Our findings suggest for the first time recent stressors distinguished suicide ideating controls from suicide decedents in the month prior to death as reported by informants. Implications for preventive intervention efforts for clinicians, supervisors and family members in identifying the transition from ideation to action are discussed.

Abstract Theta-burst stimulation (TBS) represents a brain stimulation technique effective for treatment-resistant depression (TRD) as underlined by meta-analyses. While the methodology undergoes constant refinement, bilateral stimulation of the dorsolateral prefrontal cortex (DLPFC) appears promising to restore left DLPFC hypoactivity and right hyperactivity found in depression. The post-synaptic inhibitory serotonin-1A (5-HT1A) receptor, also occurring in the DLPFC, might be involved in this mechanism of action. To test this hypothesis, we performed PET-imaging using the tracer [carbonyl-11C]WAY-100635 including arterial blood sampling before and after a three-week treatment with TBS in 11 TRD patients compared to sham stimulation (n = 8 and n = 3, respectively). Treatment groups were randomly assigned, and TBS protocol consisted of excitatory intermittent TBS to the left and inhibitory continuous TBS to the right DLPFC. A linear mixed model including group, hemisphere, time, and Hamilton Rating Scale for Depression (HAMD) score revealed a 3-way interaction effect of group, time, and HAMD on specific distribution volume (VS) of 5-HT1A receptor. While post-hoc comparisons showed no significant changes of 5-HT1A receptor VS in either group, higher 5-HT1A receptor VS after treatment correlated with greater difference in HAMD (r = −0.62). The results of this proof-of-concept trial hint towards potential effects of TBS on the distribution of the 5-HT1A receptor. Due to the small sample size, all results must, however, be regarded with caution.

Abstract Many patients with mild traumatic brain injury (mTBI) are at risk for mental health problems such as posttraumatic stress disorder (PTSD). The objective of this study was to determine whether the polygenic risk for PTSD (or for related mental health disorders or traits including major depressive disorder [MDD] and neuroticism [NEU]) was associated with an increased likelihood of PTSD in the aftermath of mTBI. We used data from individuals of European ancestry with mTBI enrolled in TRACK-TBI (n = 714), a prospective longitudinal study of level 1 trauma center patients. One hundred and sixteen mTBI patients (16.3%) had probable PTSD (PCL-5 score ≥33) at 6 months post-injury. We used summary statistics from recent GWAS studies of PTSD, MDD, and NEU to generate polygenic risk scores (PRS) for individuals in our sample. A multivariable model that included age, sex, pre-injury history of mental disorder, and cause of injury explained 7% of the variance in the PTSD outcome; the addition of the PTSD-PRS (and five ancestral principal components) significantly increased the variance explained to 11%. The adjusted odds of PTSD in the uppermost PTSD-PRS quintile was nearly four times higher (aOR = 3.71, 95% CI 1.80–7.65) than in the lowest PTSD-PRS quintile. There was no evidence of a statistically significant interaction between PTSD-PRS and prior history of mental disorder, indicating that PTSD-PRS had similar predictive utility among those with and without pre-injury psychiatric illness. When added to the model, neither MDD-PRS nor NEU-PRS were significantly associated with the PTSD outcome. These findings show that the risk for PTSD in the context of mTBI is, in part, genetically influenced. They also raise the possibility that an individual’s PRS could be clinically actionable if used—possibly with other non-genetic predictors—to signal the need for enhanced follow-up and early intervention; this precision medicine approach needs to be prospectively studied.

Cognitive impairments are a key feature of psychopathology. Here, authors exploit the genetic overlap between cognitive dimensions and psychopathology to parse the biology of psychiatric illness and identify “meta-loci” genome segments characterized by specific patterns of overlap.

The role of the immune system in the pathogenesis of psychiatric disorders is unclear. Here, the authors show that genetic risk variants for multiple psychiatric disorders are enriched in regions of the genome active in the brain and in lymphoid cells, especially stimulated T cells, but not in myeloid cells.

Abstract Background Gastric cancer is a heterogeneous disease with poorly understood genetic and microenvironmental factors. Mutations in collagen genes are associated with genetic diseases that compromise tissue integrity, but their role in tumor progression has not been extensively reported. Aberrant collagen expression has been long associated with malignant tumor growth, invasion, chemoresistance, and patient outcomes. We hypothesized that somatic mutations in collagens could functionally alter the tumor extracellular matrix. Methods We used publicly available datasets including The Tumor Cancer Genome Atlas (TCGA) to interrogate somatic mutations in collagens in stomach adenocarcinomas. To demonstrate that collagens were significantly mutated above background mutation rates, we used a moderated Kolmogorov-Smirnov test along with combination analysis with a bootstrap approach to define the background accounting for mutation rates. Association between mutations and clinicopathological features was evaluated by Fisher or chi-squared tests. Association with overall survival was assessed by Kaplan-Meier and the Cox-Proportional Hazards Model. Gene Set Enrichment Analysis was used to interrogate pathways. Immunohistochemistry and in situ hybridization tested expression of COL7A1 in stomach tumors. Results In stomach adenocarcinomas, we identified individual collagen genes and sets of collagen genes harboring somatic mutations at a high frequency compared to background in both microsatellite stable, and microsatellite instable tumors in TCGA. Many of the missense mutations resemble the same types of loss of function mutations in collagenopathies that disrupt tissue formation and destabilize cells providing guidance to interpret the somatic mutations. We identified combinations of somatic mutations in collagens associated with overall survival, with a distinctive tumor microenvironment marked by lower matrisome expression and immune cell signatures. Truncation mutations were strongly associated with improved outcomes suggesting that loss of expression of secreted collagens impact tumor progression and treatment response. Germline collagenopathy variants guided interpretation of impactful somatic mutations on tumors. Conclusions These observations highlight that many collagens, expressed in non-physiologically relevant conditions in tumors, harbor impactful somatic mutations in tumors, suggesting new approaches for classification and therapy development in stomach cancer. In sum, these findings demonstrate how classification of tumors by collagen mutations identified strong links between specific genotypes and the tumor environment.

Background: Serotonergic agents affect brain plasticity and reverse stress-induced dendritic atrophy in key fronto-limbic brain areas associated with learning and memory. Objectives: The aim of this study was to investigate effects of the antidepressant escitalopram on gray matter during relearning in healthy individuals to inform a model for depression and the neurobiological processes of recovery. Design: Randomized double blind placebo control, monocenter study. Methods: In all, 76 (44 females) healthy individuals performed daily an associative learning task with emotional or non-emotional content over a 3-week period. This was followed by a 3-week relearning period (randomly shuffled association within the content group) with concurrent daily selective serotonin reuptake inhibitor (i.e., 10 mg escitalopram) or placebo intake. Results: Via voxel-based morphometry and only in individuals that developed sufficient escitalopram blood levels over the 21-day relearing period, an increased density of the left dorsolateral prefrontal cortex was found. When investigating whether there was an interaction between relearning and drug intervention for all participants, regardless of escitalopram levels, no changes in gray matter were detected with either surfaced-based or voxel-based morphometry analyses. Conclusion: The left dorsolateral prefrontal cortex affects executive function and emotional processing, and is a critical mediator of symptoms and treatment outcomes of depression. In line, the findings suggest that escitalopram facilitates neuroplastic processes in this region if blood levels are sufficient. Contrary to our hypothesis, an effect of escitalopram on brain structure that is dependent of relearning content was not detected. However, this may have been a consequence of the intensity and duration of the interventions. Registration: ClinicalTrials.gov Identifier: NCT02753738; Trial Name: Enhancement of learning associated neural plasticity by Selective Serotonin Reuptake Inhibitors ; URL: https://clinicaltrials.gov/ct2/show/NCT02753738 .

Abstract The goal of this study was to compare brain structure between individuals with generalized anxiety disorder (GAD) and healthy controls. Previous studies have generated inconsistent findings, possibly due to small sample sizes, or clinical/analytic heterogeneity. To address these concerns, we combined data from 28 research sites worldwide through the ENIGMA-Anxiety Working Group, using a single, pre-registered mega-analysis. Structural magnetic resonance imaging data from children and adults (5–90 years) were processed using FreeSurfer. The main analysis included the regional and vertex-wise cortical thickness, cortical surface area, and subcortical volume as dependent variables, and GAD, age, age-squared, sex, and their interactions as independent variables. Nuisance variables included IQ, years of education, medication use, comorbidities, and global brain measures. The main analysis (1020 individuals with GAD and 2999 healthy controls) included random slopes per site and random intercepts per scanner. A secondary analysis (1112 individuals with GAD and 3282 healthy controls) included fixed slopes and random intercepts per scanner with the same variables. The main analysis showed no effect of GAD on brain structure, nor interactions involving GAD, age, or sex. The secondary analysis showed increased volume in the right ventral diencephalon in male individuals with GAD compared to male healthy controls, whereas female individuals with GAD did not differ from female healthy controls. This mega-analysis combining worldwide data showed that differences in brain structure related to GAD are small, possibly reflecting heterogeneity or those structural alterations are not a major component of its pathophysiology.

Objectives Patients with systemic lupus erythematosus (SLE) are usually treated with glucocorticosteroids even during periods of clinically quiescent disease. A recent study showed that abrupt glucocorticoid withdrawal was associated with an increased likelihood of flare in the next 12 months. The aim of the present study was to assess clinical flare rates and damage accrual in patients who tapered glucocorticosteroids gradually. Methods Patients from the Toronto Lupus Clinic with 2 consecutive years of clinically quiescent disease were retrieved from the database. Individuals who maintained a low prednisone dose (5 mg/day) comprised the maintenance group, whereas patients who gradually tapered prednisone within these two years comprised the withdrawal group. All individuals were followed for 2 years after prednisone discontinuation or the corresponding date for the maintenance group. Propensity score matching was implemented to adjust for certain baseline differences. Outcomes included clinical flares and damage accrual. Results Of 270 eligible patients, 204 were matched (102 in each group). Flare rate (any increase in clinical SLE Disease Activity Index 2000) was lower in the withdrawal group both at 12 (17.6% versus 29.4%; P = 0.023) and 24 months (33.3% versus 50%; P = 0.01). Moderate to severe flares (requiring systemic treatment escalation) were not different at 12 months (10.8% versus 13.7%; P = 0.467) but were less frequent at 24 months (14.7% versus 27.5%; P = 0.024). Damage accrual was less frequent in the withdrawal group (6.9% versus 17.6%; P = 0.022). No predictors for clinical flares were identified. Conclusion Gradual glucocorticoid withdrawal is safe in clinically quiescent SLE and is associated with fewer clinical flares and less damage accrual at 24 months.

Computational methods have made progress in improving classification accuracy and throughput of pathology workflows, but lack of interpretability remains a barrier to clinical integration. Here, the authors present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features.

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.

Abstract Substance dependence diagnoses (SDs) are important risk factors for suicidality. We investigated the associations of multiple SDs with different suicidality outcomes, testing how genetic background moderates these associations. The Yale-Penn cohort (N = 15,557) was recruited to investigate the genetics of SDs. The Army STARRS (Study to Assess Risk and Resilience in Servicemembers) cohort (N = 11,236) was recruited to evaluate mental health risk and resilience among Army personnel. We applied multivariate logistic regression to investigate the associations of SDs with suicidality and, in the Yale-Penn cohort, we used the structured linear mixed model (StructLMM) to study multivariate gene–environment interactions. In Yale-Penn, lifetime polysubstance dependence was strongly associated with lifetime suicidality: having five SDs showed an association with suicidality, from odds ratio (OR) = 6.77 (95% confidence interval, CI = 5.74–7.99) for suicidal ideation (SI) to OR = 3.61 (95% CI = 2.7–4.86) for suicide attempt (SA). In Army STARRS, having multiple substance use disorders for alcohol and/or drugs was associated with increased suicidality ranging from OR = 2.88 (95% CI = 2.6–3.19) for SI to OR = 3.92 (95% CI = 3.19–4.81) for SA. In Yale-Penn, we identified multivariate gene–environment interactions (Bayes factors, BF > 0) of SI with respect to a gene cluster on chromosome 16 (LCAT, p = 1.82 × 10–7; TSNAXIP1, p = 2.13 × 10−7; CENPT, p = 2.32 × 10−7; PARD6A, p = 5.57 × 10−7) for opioid dependence (BF = 12.2), cocaine dependence (BF = 12.1), nicotine dependence (BF = 9.2), and polysubstance dependence (BF = 2.1). Comorbidity of multiple SDs is a significant associated with suicidality and heritability of suicidality is partially moderated by multivariate gene interactions.

Abstract Objectives Type I interferons (IFNs) play an important role in the pathophysiology of systemic lupus erythematosus (SLE). While cross-sectional data suggest an association between IFN-induced gene expression and SLE disease activity, interest in this as a biomarker of flare has been tempered by a lack of fluctuation with disease activity in the majority of patients. This led us to question whether IFN-induced gene expression might instead be a biomarker of overall disease severity, with patients with high levels spending more time in an active disease state. Methods Levels of five interferon-responsive genes were measured in the whole peripheral blood at baseline visit for 137 SLE patients subsequently followed for 5 years. Log transformed values were summed to yield a composite IFN5 score, and the correlation with various disease outcomes examined. Receiver operator characteristic analyses were performed for outcomes of interest. Kaplan-Meier curves were generated to compare the proportion of flare-free patients with high and low IFN5 scores over time. Results The baseline IFN5 score was positively correlated with the adjusted mean SLE disease activity index-2000, number of flares, adjusted mean prednisone dose, and number of new immunosuppressive medications over the subsequent 5 years. Optimal cut-offs for the IFN5 score were determined using Youden’s index and predicted more severe outcomes with 57–67% accuracy. A high baseline IFN5 level was associated with a significantly increased risk of subsequent flare. Conclusions Measurement of the type I IFN signature is a useful tool for predicting the subsequent disease activity course.

PTSD has been associated with DNA methylation of specific loci in the genome, but studies have been limited by small sample sizes. Here, the authors perform a meta-analysis of DNA methylation data from 10 different cohorts and identify CpGs in AHRR that are associated with PTSD.

Abstract Background While surgery is the first-line treatment for patients with endogenous hypercortisolism (Cushing syndrome [CS]), mifepristone has been shown to be a beneficial medical treatment option, as demonstrated in the SEISMIC (Study of the Efficacy and Safety of Mifepristone in the Treatment of Endogenous Cushing Syndrome) trial. Mifepristone is a competitive glucocorticoid receptor antagonist and progesterone receptor antagonist that is associated with several treatment effects and adverse events that clinicians need to be aware of when considering its use. The objective of this review was to provide updated clinical management recommendations for patients with CS treated with mifepristone. Methods A panel of endocrinologists from the US with extensive experience in treating patients with CS, including with mifepristone, convened as part of a clinical advisory board to develop a consensus on the practical, real-world clinical management of patients on mifepristone. Results Comprehensive considerations and recommendations are provided for managing mifepristone-associated effects, including symptoms of cortisol withdrawal, hypokalemia, and change in thyroid function; effects related to its antiprogesterone activity; and rash. Additional management strategies to address concomitant medications and special clinical situations, such as surgery and use in specific populations, are also provided. Conclusion Safe and effective use of mifepristone requires clinical judgment and close patient monitoring to ensure optimal clinical outcomes. These consensus recommendations provide useful, practical guidance to clinicians using mifepristone.

The diamondback moth, Plutella xylostella is a cosmopolitan agricultural pest. By analyzing 532 genomes from 114 populations around the world, the authors find evidence supporting a South American origin of this moth, and look for signatures of positive selection.

Summary: Background: Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias. Methods: We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography. Findings: The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10−8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10−5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10−4). Interpretation: While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available. Funding: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Background: Posttraumatic stress disorder (PTSD) is triggered by environmental stressors. Empathy may predispose an individual to respond to life events differently if high empathizers are emotionally more sensitive to trauma. For the first time, we test this hypothesis using genetic information. Methods: We applied polygenic scoring (PGS) to investigate the shared genetics linking empathy (measured using the Empathy Quotient (EQ), a self-report measure of empathy; N = 46,861) and PTSD symptom severity (measured using the 6-item PTSD Checklist 6-item (PCL-6)) in the UK Biobank (N = 126,219). Follow-up analyses were performed in the context of (1) experiencing any of 16 potential traumas, (2) the total number of traumas endorsed, and (3) the context of trauma. Autism, depression, generalized anxiety, and PCL-17 PGS were included as covariates to verify the specificity of the effect. Results: EQPGS associated with PCL-6 (R2 = 0.012%, P = 9.35 × 10−5). This effect remained significant after accounting for autism, depression, PTSD, and anxiety PGS but was observed only in those who endorsed experiencing at least one traumatic event. EQPGS showed the strongest effect on PCL-6 (β = 2.32, s.e. = 0.762, P = 0.002) among those who endorsed childhood neglect/abuse (felt hated as a child). With respect to case status, the highest probability of PTSD was 17.93% and 10.04% for those who endorsed “feeling hated as a child” and those who did not, respectively (Pdiff = 0.011; Cohen's d = 1.951, 95%CI 1.70–2.20). Conclusions: A genetic predisposition to higher empathy, which may index greater emotional sensitivity, predisposes an individual to more severe PTSD symptoms, especially after early-life adversity.

The accurate segmentation of in vivo magnetic resonance imaging (MRI) data is a crucial prerequisite for the reliable assessment of disease progression, patient stratification or the establishment of putative imaging biomarkers. This is especially important for the hippocampal formation, a brain area involved in memory formation and often affected by neurodegenerative or psychiatric diseases. FreeSurfer, a widely used automated segmentation software, offers hippocampal subfield delineation with multiple input options. While a single T1-weighted (T1) sequence is regularly used by most studies, it is also possible and advised to use a high-resolution T2-weighted (T2H) sequence or multispectral information. In this investigation it was determined whether there are differences in volume estimations depending on the input images and which combination of these deliver the most reliable results in each hippocampal subfield. 41 healthy participants (age = 25.2 years ± 4.2 SD) underwent two structural MRIs at three Tesla (time between scans: 23 days ± 11 SD) using three different structural MRI sequences, to test five different input configurations (T1, T2, T2H, T1 and T2, and T1 and T2H). We compared the different processing pipelines in a cross-sectional manner and assessed reliability using test-retest variability (%TRV) and the dice coefficient. Our analyses showed pronounced significant differences and large effect sizes between the processing pipelines in several subfields, such as the molecular layer (head), CA1 (head), hippocampal fissure, CA3 (head and body), fimbria and CA4 (head). The longitudinal analysis revealed that T1 and multispectral analysis (T1 and T2H) showed overall higher reliability across all subfields than T2H alone. However, the specific subfields had a substantial influence on the performance of segmentation results, regardless of the processing pipeline. Although T1 showed good test-retest metrics, results must be interpreted with caution, as a standard T1 sequence relies heavily on prior information of the atlas and does not take the actual fine structures of the hippocampus into account. For the most accurate segmentation, we advise the use of multispectral information by using a combination of T1 and high-resolution T2-weighted sequences or a T2 high-resolution sequence alone.

Abstract Background Cytokeratin 7 (CK7) and GATA binding protein 3 (GATA3) are considered as immunohistochemical hallmarks of breast cancers; however, there are breast tumors lacking these markers. Clinicopathological characterization of CK7 negative breast cancer has not been addressed previously and similar studies on GATA3 negative tumors are limited. Methods This study included 196 consecutive cases of Nottingham Grade 3 breast cancers with 159 cases of Grade 1 and Grade 2 tumors for comparison. CK7 and GATA3 expression was correlated with patient’s age, histological type, pathological grade and stage, hormone receptor status, molecular subtype and overall survival. Results CK7 negativity was seen in 13% of Grade 3, 9% of Grade 2, and 2% of Grade 1 cases (P = 0.0457). Similarly, 28% of Grade 3, 5% of Grade 2 and 2% of Grade 1 cases were GATA3 negative (P

Abstract Background The breast cancer microenvironment contributes to tumor progression and response to chemotherapy. Previously, we reported that increased stromal Type X collagen α1 (ColXα1) and low TILs correlated with poor pathologic response to neoadjuvant therapy in estrogen receptor and HER2-positive (ER+/HER2+) breast cancer. Here, we investigate the relationship of ColXα1 and long-term outcome of ER+/HER2+ breast cancer patients in an adjuvant setting. Methods A total of 164 cases with at least 5-year follow-up were included. Immunohistochemistry for ColXα1 was performed on whole tumor sections. Associations between ColXα1expression, clinical pathological features, and outcomes were analyzed. Results ColXα1 expression was directly proportional to the amount of tumor associated stroma (p = 0.024) and inversely proportional to TILs. Increased ColXα1 was significantly associated with shorter disease free survival and overall survival by univariate analysis. In multivariate analysis, OS was lower in ColXα1 expressing (HR = 2.1; 95% CI = 1.2–3.9) tumors of older patients (> = 58 years) (HR = 5.3; 95% CI = 1.7–17) with higher stage (HR = 2.6; 95% CI = 1.3–5.2). Similarly, DFS was lower in ColXα1 expressing (HR = 1.8; 95% CI = 1.6–5.7) tumors of older patients (HR = 3.2; 95% CI = 1.3–7.8) with higher stage (HR = 2.7; 95% CI = 1.6–5.7) and low TILs. In low PR+ tumors, higher ColXα1 expression was associated with poorer prognosis. Conclusion ColXα1 expression is associated with poor disease free survival and overall survival in ER+/HER2+ breast cancer. This study provides further support for the prognostic utility of ColXα1 as a breast cancer associated stromal factor that predicts response to chemotherapy.

Post-traumatic stress disorder (PTSD) is a common mental health problem. Here, the authors report a GWAS from the Psychiatric Genomics Consortium in which they identify two risk loci in European ancestry and one locus in African ancestry individuals and find that PTSD is genetically correlated with several other psychiatric traits.

Posttraumatic stress disorder (PTSD) is a complex psychiatric disorder that can develop following exposure to traumatic events. The Psychiatric Genomics Consortium PTSD group (PGC-PTSD) has collected over 20,000 multi-ethnic PTSD cases and controls and has identified both genetic and epigenetic factors associated with PTSD risk. To further investigate biological correlates of PTSD risk, we examined three PGC-PTSD cohorts comprising 977 subjects to identify differentially expressed genes among PTSD cases and controls. Whole blood gene expression was quantified with the HumanHT-12 v4 Expression BeadChip for 726 OEF/OIF veterans from the Veterans Affairs (VA) Mental Illness Research Education and Clinical Center (MIRECC), 155 samples from the Injury and Traumatic Stress (INTRuST) Clinical Consortium, and 96 Australian Vietnam War veterans. Differential gene expression analysis was performed in each cohort separately followed by meta-analysis. In the largest cohort, we performed co-expression analysis to identify modules of genes that are associated with PTSD and MDD. We then conducted expression quantitative trait loci (eQTL) analysis and assessed the presence of eQTL interactions involving PTSD and major depressive disorder (MDD). Finally, we utilized PTSD and MDD GWAS summary statistics to identify regions that colocalize with eQTLs. Although not surpassing correction for multiple testing, the most differentially expressed genes in meta-analysis were interleukin-1 beta (IL1B), a pro-inflammatory cytokine previously associated with PTSD, and integrin-linked kinase (ILK), which is highly expressed in brain and can rescue dysregulated hippocampal neurogenesis and memory deficits. Pathway analysis revealed enrichment of toll-like receptor (TLR) and interleukin-1 receptor genes, which are integral to cellular innate immune response. Co-expression analysis identified four modules of genes associated with PTSD, two of which are also associated with MDD, demonstrating common biological pathways underlying the two conditions. Lastly, we identified four genes (UBA7, HLA-F, HSPA1B, and RERE) with high probability of a shared causal eQTL variant with PTSD and/or MDD GWAS variants, thereby providing a potential mechanism by which the GWAS variant contributes to disease risk. In summary, we provide additional evidence for genes and pathways previously reported and identified plausible novel candidates for PTSD. These data provide further insight into genetic factors and pathways involved in PTSD, as well as potential regions of pleiotropy between PTSD and MDD.

Introduction/PurposeRelacorilant is a selective glucocorticoid receptor modulator (SGRM) with no progesterone receptor activity. We evaluated the efficacy and safety of relacorilant in patients with endogenous Cushing syndrome (CS).Materials and MethodsA single-arm, open-label, phase 2, dose-finding study with 2 dose groups (NCT02804750, https://clinicaltrials.gov/ct2/show/NCT02804750) was conducted at 19 sites in the U.S. and Europe. Low-dose relacorilant (100-200 mg/d; n = 17) was administered for 12 weeks or high-dose relacorilant (250-400 mg/d; n = 18) for 16 weeks; doses were up-titrated by 50 mg every 4 weeks. Outcome measures included proportion of patients with clinically meaningful changes in hypertension and/or hyperglycemia from baseline to last observed visit. For patients with hypertension, clinical response was defined as a ≥5-mmHg decrease in mean systolic or diastolic blood pressure, measured by a standardized and validated 24-h ABPM. For patients with hyperglycemia, clinical response was defined ad-hoc as ≥0.5% decrease in HbA1c, normalization or ≥50-mg/dL decrease in 2-h plasma glucose value on oral glucose tolerance test, or decrease in daily insulin (≥25%) or sulfonylurea dose (≥50%).Results35 adults with CS and hypertension and/or hyperglycemia (impaired glucose tolerance or type 2 diabetes mellitus) were enrolled, of which 34 (24 women/10 men) received treatment and had postbaseline data. In the low-dose group, 5/12 patients (41.7%) with hypertension and 2/13 patients (15.4%) with hyperglycemia achieved response. In the high-dose group, 7/11 patients (63.6%) with hypertension and 6/12 patients (50%) with hyperglycemia achieved response. Common (≥20%) adverse events included back pain, headache, peripheral edema, nausea, pain at extremities, diarrhea, and dizziness. No drug-induced vaginal bleeding or hypokalemia occurred.ConclusionsThe SGRM relacorilant provided clinical benefit to patients with CS without undesirable antiprogesterone effects or drug-induced hypokalemia.

Epidemiologic studies recognize that trauma and posttraumatic stress are associated with heightened suicidal behavior severity, yet examination of these associations from a genetic perspective is limited. We performed a multivariate gene-by-environment genome-wide interaction study (GEWIS) of suicidality in 123,633 individuals using a covariance matrix based on 26 environments related to traumatic experiences, posttraumatic stress, social support, and socioeconomic status. We discovered five suicidality risk loci, including the male-associated rs2367967 (CWC22), which replicated in an independent cohort. All GEWIS-significant loci exhibited interaction effects where at least 5% of the sample had environmental profiles conferring opposite SNP effects from the majority. We identified PTSD as a primary driving environment for GxE at suicidality risk loci. The male suicidality GEWIS was enriched for three middle-temporal-gyrus inhibitory neuron transcriptomic profiles: SCUBE- and PVALB-expressing cells (β = 0.028, p = 3.74 × 10−4), OPRM1-expressing cells (β = 0.030, p = 0.001), and SPAG17-expressing cells (β = 0.029, p = 9.80 × 10−4). Combined with gene-based analyses (CNTN5 passociation = 2.38 × 10−9, pinteraction = 1.51 × 10−3; PSMD14 passociation = 2.04 × 10−7, pinteraction = 7.76 × 10−6; HEPACAM passociation = 2.43 × 10−6, pinteraction = 3.82 × 10−7) including information about brain chromatin interaction profiles (UBE2E3 in male neuron p = 1.07 × 10−5), our GEWIS points to extracellular matrix biology and synaptic plasticity as biological interactors with the effects of potentially modifiable lifetime traumatic experiences on genetic risk for suicidality. Characterization of molecular basis for the effects of traumatic experience and posttraumatic stress on risk of suicidal behaviors may help to identify novel targets for which more effective treatments can be developed for use in high-risk populations.

Medical treatment for acromegaly commonly involves receiving intramuscular or deep subcutaneous injections of somatostatin receptor ligands (SRLs) in most patients. In addition to side effects of treatment, acromegaly patients often still experience disease symptoms even when therapy is successful in controlling GH and IGF-1 levels. Symptoms and side effects can negatively impact patients’ health-related quality of life. In this study, we examine the disease- and treatment-related burden associated with SRL injections as reported through the use of the Acromegaly Treatment Satisfaction Questionnaire (Acro-TSQ ©) and clinician-reported symptom severity through the Acromegaly Index of Severity (AIS). Patients included in this analysis were enrolled in a randomized phase 3 study, were biochemically-controlled (an IGF-1 < 1.3 × the upper limit of normal [ULN] and average GH < 2.5 ng/ml) and receiving SRL injections for ≥6 months with a stable dose of either long-acting octreotide or lanreotide monotherapy for ≥4 months. The sample (N = 91) was 65% female, 91% Caucasian, with a mean [standard deviation (SD)] age of 53 (1) years. Two-thirds of patients reported that they still experience acromegaly symptoms; 82% of these said they experience symptoms all of the time. Three-fourths experienced gastrointestinal (GI) side effects after injections, and 77% experienced treatment-related injection site reactions (ISRs). Patients commonly reported that these interfered with their daily life, leisure, and work activities. Those with higher symptom severity, as measured by the AIS, scored significantly worse on several Acro-TSQ domains: Symptom Interference, GI Interference, Treatment Satisfaction, and Emotional Reaction. Despite being biochemically controlled with injectable SRLs, most patients reported experiencing acromegaly symptoms that interfere with daily life, leisure, and work. GI side effects and ISRs were also common. This study highlights the significant disease burden that still persists for patients with acromegaly that have achieved biochemical control with the use of injectable SRLs.

Abstract Background Although the majority of active duty U.S. Army soldiers are full-time personnel in the Active Component (AC), a substantial minority of soldiers on active duty are in the Reserve Components (RCs). These “citizen-soldiers” (Army National Guard and Army Reserve) represent a force available for rapid activation in times of national need. RC soldiers experience many of the same stressors as AC soldiers as well as stressors that are unique to their intermittent service. Despite the important role of RC soldiers, the vast majority of military mental health research focuses on AC soldiers. One important goal of the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS) is to address this gap. Here we examine predictors of suicide attempts among activated RC soldiers. Methods This longitudinal, retrospective cohort study used individual-level person-month records from Army and Department of Defense administrative data systems to examine socio-demographic, service-related, and mental health predictors of medically documented suicide attempts among activated RC soldiers during 2004–2009. Data from all 1103 activated RC suicide attempters and an equal-probability sample of 69,867 control person-months were analyzed using a discrete-time survival framework. Results Enlisted soldiers comprised 84.3% of activated RC soldiers and accounted for 95.7% of all activated RC suicide attempts (overall rate = 108/100,000 person-years, more than four times the rate among officers). Multivariable predictors of enlisted RC suicide attempts included being female, entering Army service at age ≥ 25, current age

ABSTRACT: Objective: We report the first case of recurrent ductal breast carcinoma presenting as primary adrenal insufficiency. Methods: We describe a patient who developed a recurrence of invasive ductal breast carcinoma which went undetected until the patient presented with fulminant adrenal crisis. We describe here an overview of the clinical presentation, work-up, diagnosis, and treatment of adrenal crisis. Results: Adrenal crisis due to bilateral adrenal metastases secondary to invasive ductal breast carcinoma is an exceedingly rare occurrence. To our knowledge, this is the first case of recurrent breast carcinoma in which the presenting feature is primary adrenal insufficiency. Conclusion: Patients with a history of breast carcinoma and bilateral adrenal enlargement should be evaluated for the presence of primary adrenal insufficiency.

Abstract Background High rates of mental disorders, suicidality, and interpersonal violence early in the military career have raised interest in implementing preventive interventions with high-risk new enlistees. The Army Study to Assess Risk and Resilience in Servicemembers (STARRS) developed risk-targeting systems for these outcomes based on machine learning methods using administrative data predictors. However, administrative data omit many risk factors, raising the question whether risk targeting could be improved by adding self-report survey data to prediction models. If so, the Army may gain from routinely administering surveys that assess additional risk factors. Methods The STARRS New Soldier Survey was administered to 21,790 Regular Army soldiers who agreed to have survey data linked to administrative records. As reported previously, machine learning models using administrative data as predictors found that small proportions of high-risk soldiers accounted for high proportions of negative outcomes. Other machine learning models using self-report survey data as predictors were developed previously for three of these outcomes: major physical violence and sexual violence perpetration among men and sexual violence victimization among women. Here we examined the extent to which this survey information increases prediction accuracy, over models based solely on administrative data, for those three outcomes. We used discrete-time survival analysis to estimate a series of models predicting first occurrence, assessing how model fit improved and concentration of risk increased when adding the predicted risk score based on survey data to the predicted risk score based on administrative data. Results The addition of survey data improved prediction significantly for all outcomes. In the most extreme case, the percentage of reported sexual violence victimization among the 5% of female soldiers with highest predicted risk increased from 17.5% using only administrative predictors to 29.4% adding survey predictors, a 67.9% proportional increase in prediction accuracy. Other proportional increases in concentration of risk ranged from 4.8% to 49.5% (median = 26.0%). Conclusions Data from an ongoing New Soldier Survey could substantially improve accuracy of risk models compared to models based exclusively on administrative predictors. Depending upon the characteristics of interventions used, the increase in targeting accuracy from survey data might offset survey administration costs.