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.

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.

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 χ 21 = 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.

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.

Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.

This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.

The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).

Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.

Parkinsonism and Parkinson's disease (PD) have been described as consequences of repetitive head impacts (RHI) from boxing, since 1928. Autopsy studies have shown that RHI from other contact sports can also increase risk for neurodegenerative diseases, including chronic traumatic encephalopathy (CTE) and Lewy bodies. In vivo research on the relationship between American football play and PD is scarce, with small samples, and equivocal findings. This study leveraged the Fox Insight study to evaluate the association between American football and parkinsonism and/or PD Diagnosis and related clinical outcomes.

Fox Insight is an online study of people with and without PD who are 18+ years (>50,000 enrolled). Participants complete online questionnaires on motor function, cognitive function, and general health behaviors. Participants self-reported whether they "currently have a diagnosis of Parkinson's disease, or parkinsonism, by a physician or other health care professional." In November 2020, the Boston University Head Impact Exposure Assessment was launched in Fox Insight for large-scale data collection on exposure to RHI from contact sports and other sources. Data used in this abstract were obtained from the Fox Insight database https://foxinsight-info.michaeljfox.org/insight/explore/insight.jsp on 01/06/2022. The sample includes 2018 men who endorsed playing an organized sport. Because only 1.6% of football players were women, analyses are limited to men. Responses to questions regarding history of participation in organized football were examined. Other contact and/or non-contact sports served as the referent group. Outcomes included PD status (absence/presence of parkinsonism or PD) and Penn Parkinson's Daily Activities Questionnaire-15 (PDAQ-15) for assessment of cognitive symptoms. Binary logistic regression tested associations between history and years of football play with PD status, controlling for age, education, current heart disease or diabetes, and family history of PD. Linear regressions, controlling for these variables, were used for the PDAQ-15.

Of the 2018 men (mean age=67.67, SD=9.84; 10, 0.5% Black), 788 (39%) played football (mean years of play=4.29, SD=2.88), including 122 (16.3%) who played youth football, 494 (66.0%) played high school, 128 (17.1%) played college football, and 5 (0.7%) played at the semi-professional or professional level. 1738 (86.1%) reported being diagnosed with parkinsonism/PD, and 707 of these were football players (40.7%). History of playing any level of football was associated with increased odds of having a reported parkinsonism or PD diagnosis (OR=1.52, 95% CI=1.14-2.03, p=0.004). The OR remained similar among those age <69 (sample median age) (OR=1.45, 95% CI=0.97-2.17, p=0.07) and 69+ (OR=1.45, 95% CI=0.95-2.22, p=0.09). Among the football players, there was not a significant association between years of play and PD status (OR=1.09, 95% CI=1.00-1.20, p=0.063). History of football play was not associated with PDAQ-15 scores (n=1980) (beta=-0.78, 95% CI=-1.59-0.03, p=0.059) among the entire sample.

Among 2018 men from a data set enriched for PD, playing organized football was associated with increased odds of having a reported parkinsonism/PD diagnosis. Next steps include examination of the contribution of traumatic brain injury and other sources of RHI (e.g., soccer, military service).

Former professional American football players have a high relative risk for neurodegenerative diseases like chronic traumatic encephalopathy (CTE). Interpreting low cognitive test scores in this population occasionally is complicated by performance on validity testing. Neuroimaging biomarkers may help inform whether a neurodegenerative disease is present in these situations. We report three cases of retired professional American football players who completed comprehensive neuropsychological testing, but “failed” performance validity tests, and underwent multimodal neuroimaging (structural MRI, Aß-PET, and tau-PET).

Three cases were identified from the Focused Neuroimaging for the Neurodegenerative Disease Chronic Traumatic Encephalopathy (FIND-CTE) study, an ongoing multimodal imaging study of retired National Football League players with complaints of progressive cognitive decline conducted at Boston University and the UCSF Memory and Aging Center. Participants were relatively young (age range 55-65), had 16 or more years of education, and two identified as Black/African American. Raw neuropsychological test scores were converted to demographically-adjusted z-scores. Testing included standalone (Test of Memory Malingering; TOMM) and embedded (reliable digit span, RDS) performance validity measures. Validity cutoffs were TOMM Trial 2 < 45 and RDS < 7. Structural MRIs were interpreted by trained neurologists. Aß-PET with Florbetapir was used to quantify cortical Aß deposition as global Centiloids (0 = mean cortical signal for a young, cognitively normal, Aß negative individual in their 20s, 100 = mean cortical signal for a patient with mild-to-moderate Alzheimer’s disease dementia). Tau-PET was performed with MK-6240 and first quantified as standardized uptake value ratio (SUVR) map. The SUVR map was then converted to a w-score map representing signal intensity relative to a sample of demographically-matched healthy controls.

All performed in the average range on a word reading-based estimate of premorbid intellect. Contribution of Alzheimer’s disease pathology was ruled out in each case based on Centiloids quantifications < 0. All cases scored below cutoff on TOMM Trial 2 (Case #1=43, Case #2=42, Case #3=19) and Case #3 also scored well below RDS cutoff (2). Each case had multiple cognitive scores below expectations (z < -2.0) most consistently in memory, executive function, processing speed domains. For Case #1, MRI revealed mild atrophy in dorsal fronto-parietal and medial temporal lobe (MTL) regions and mild periventricular white matter disease. Tau-PET showed MTL tau burden modestly elevated relative to controls (regional w-score=0.59, 72nd%ile). For Case #2, MRI revealed cortical atrophy, mild hippocampal atrophy, and a microhemorrhage, with no evidence of meaningful tau-PET signal. For Case #3, MRI showed cortical atrophy and severe white matter disease, and tau-PET revealed significantly elevated MTL tau burden relative to controls (w-score=1.90, 97th%ile) as well as focal high signal in the dorsal frontal lobe (overall frontal region w-score=0.64, 74th%ile).

Low scores on performance validity tests complicate the interpretation of the severity of cognitive deficits, but do not negate the presence of true cognitive impairment or an underlying neurodegenerative disease. In the rapidly developing era of biomarkers, neuroimaging tools can supplement neuropsychological testing to help inform whether cognitive or behavioral changes are related to a neurodegenerative disease.

Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).

This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.

Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.

The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that can only be diagnosed at post-mortem. Revised criteria for the clinical syndrome of CTE, known as traumatic encephalopathy syndrome (TES), include impairments in episodic memory and/or executive function as core clinical features. These criteria were informed by retrospective interviews with next-of-kin and the presence and rates of objective impairments in memory and executive functions in CTE are unknown. Here, we characterized antemortem neuropsychological test performance in episodic memory and executive functions among deceased contact sport athletes neuropathologically diagnosed with CTE.

The sample included 80 deceased male contact sport athletes from the UNITE brain bank who had autopsy-confirmed CTE (and no other neurodegenerative diseases). Published criteria were used for the autopsy diagnosis of CTE. Neuropsychological test reports (raw scores) were acquired through medical record requests. Raw scores were converted to z-scores using the same age, sex, and education-adjusted normative data. Tests of memory included long delay trials from the Rey Complex Figure, CVLT-II, HVLT-R, RBANS, and BVMT-R. Tests of executive functions included Trail Making Test-B (TMT-B), Controlled Oral Word Association Test, WAIS-III Picture Arrangement, and various WAIS-IV subtests. Not all brain donors had the same tests, and the sample sizes vary across tests, with 33 donors having tests from both domains. Twenty-eight had 1 test in memory and 3 had 2+. Eight had 1 test of executive function and 46 had 2+. A z-score of 1.5 standard deviations below the normative mean was impaired. Interpretation of test performance followed the American Academy of Clinical Neuropsychology guidelines (Guilmette et al., 2020). Bivariate correlations assessed cumulative p-tau burden (summary semiquantitative ratings of p-tau severity across 11 brain regions) and TMT-B (n=34) and CVLT-II (n=14), the most common tests available.

Of the 80 (mean age= 59.9, SD=18.0 years; 13, 16.3% were Black), 72 played football, 4 played ice hockey, and 4 played other contact sports. Most played at the professional level (57, 71.3%). Mean time between neuropsychological testing and death was 3.9 (SD= 4.5) years. The most common reason for testing was dementia-related (43, 53.8%). Mean z-scores fell in the average psychometric range(mean z= -0.52, SD=1.5, range= -6.0 to 3.0) for executive function and the low average range for memory (mean z= -1.3, SD=1.1, range= -4.0 to 2.0). Eleven (20.4%) had impairment on 1 test and 3 (5.6%) on 2+ tests of executive functions. The most common impairment was on TMT-B (mean z= -1.77, 13 [38.2%] impaired). For memory, 13 (41.9%) had impairment on 1 test. Of the 14 who had CVLT-II, 7 were impaired (mean z= -1.33). Greater p-tau burden was associated with worse performance on CVLT-II (r= -.653, p= .02), but not TMT-B (r= .187, p>.05).

This study provides the first evidence for objectively-measured impairments in executive functions and memory in a sample with known, autopsy-confirmed CTE. Furthermore, p-tau burden corresponded to worse memory test performance. Examination of neuropsychological tests from medical records has limitations but can overcome shortcomings of retrospective informant reports to provide insight into the cognitive profiles associated with CTE.

Insecure attachment styles are associated with retrospectively reported suicide attempts (SAs). It is not known if attachment styles are prospectively associated with medically documented SAs.

A representative sample of US Army soldiers entering service (n = 21 772) was surveyed and followed via administrative records for their first 48 months of service. Attachment style (secure, preoccupied, fearful, dismissing) was assessed at baseline. Administrative medical records identified SAs. Discrete-time survival analysis examined associations of attachment style with future SA during service, adjusting for time in service, socio-demographics, service-related variables, and mental health diagnosis (MH-Dx). We examined whether associations of attachment style with SA differed based on sex and MH-Dx.

In total, 253 respondents attempted suicide. Endorsed attachment styles included secure (46.8%), preoccupied (9.1%), fearful (15.7%), and dismissing (19.2%). Examined separately, insecure attachment styles were associated with increased odds of SA: preoccupied [OR 2.5 (95% CI 1.7–3.4)], fearful [OR 1.6 (95% CI 1.1–2.3)], dismissing [OR 1.8 (95% CI 1.3–2.6)]. Examining attachment styles simultaneously along with other covariates, preoccupied [OR 1.9 (95% CI 1.4–2.7)] and dismissing [OR 1.7 (95% CI 1.2–2.4)] remained significant. The dismissing attachment and MH-Dx interaction was significant. In stratified analyses, dismissing attachment was associated with SA only among soldiers without MH-Dx. Other interactions were non-significant. Soldiers endorsing any insecure attachment style had elevated SA risk across the first 48 months in service, particularly during the first 12 months.

Insecure attachment styles, particularly preoccupied and dismissing, are associated with increased future SA risk among soldiers. Elevated risk is most substantial during first year of service but persists through the first 48 months. Dismissing attachment may indicate risk specifically among soldiers not identified by the mental healthcare system.

To evaluate random effects of volume (patient days or device days) on healthcare-associated infections (HAIs) and the standardized infection ratio (SIR) used to compare hospitals.

A longitudinal comparison between publicly reported quarterly data (2014–2020) and volume-based random sampling using 4 HAI types: central-line–associated bloodstream infections, catheter-associated urinary tract infections, Clostridioides difficile infections, methicillin-resistant Staphylococcus aureus infections.

Using 4,268 hospitals with reported SIRs, we examined relationships of SIRs to volume and compared distributions of SIRs and numbers of reported HAIs to the outcomes of simulated random sampling. We included random expectations into SIR calculations to produce a standardized infection score (SIS).

Among hospitals with volumes less than the median, 20%–33% had SIRs of 0, compared to 0.3%–5% for hospitals with volumes higher than the median. Distributions of SIRs were 86%–92% similar to those based on random sampling. Random expectations explained 54%–84% of variation in numbers of HAIs. The use of SIRs led hundreds of hospitals with more infections than either expected at random or predicted by risk-adjusted models to rank better than other hospitals. The SIS mitigated this effect and allowed hospitals of disparate volumes to achieve better scores while decreasing the number of hospitals tied for the best score.

SIRs and numbers of HAIs are strongly influenced by random effects of volume. Mitigating these effects drastically alters rankings for HAI types and may further alter penalty assignments in programs that aim to reduce HAIs and improve quality of care.

Risk of suicide-related behaviors is elevated among military personnel transitioning to civilian life. An earlier report showed that high-risk U.S. Army soldiers could be identified shortly before this transition with a machine learning model that included predictors from administrative systems, self-report surveys, and geospatial data. Based on this result, a Veterans Affairs and Army initiative was launched to evaluate a suicide-prevention intervention for high-risk transitioning soldiers. To make targeting practical, though, a streamlined model and risk calculator were needed that used only a short series of self-report survey questions.

We revised the original model in a sample of n = 8335 observations from the Study to Assess Risk and Resilience in Servicemembers-Longitudinal Study (STARRS-LS) who participated in one of three Army STARRS 2011–2014 baseline surveys while in service and in one or more subsequent panel surveys (LS1: 2016–2018, LS2: 2018–2019) after leaving service. We trained ensemble machine learning models with constrained numbers of item-level survey predictors in a 70% training sample. The outcome was self-reported post-transition suicide attempts (SA). The models were validated in the 30% test sample.

Twelve-month post-transition SA prevalence was 1.0% (s.e. = 0.1). The best constrained model, with only 17 predictors, had a test sample ROC-AUC of 0.85 (s.e. = 0.03). The 10–30% of respondents with the highest predicted risk included 44.9–92.5% of 12-month SAs.

An accurate SA risk calculator based on a short self-report survey can target transitioning soldiers shortly before leaving service for intervention to prevent post-transition SA.

Identification of genetic risk factors may inform the prevention and treatment of posttraumatic stress disorder (PTSD). This study evaluates the associations of polygenic risk scores (PRS) with patterns of posttraumatic stress symptoms following combat deployment.

US Army soldiers of European ancestry (n = 4900) provided genomic data and ratings of posttraumatic stress symptoms before and after deployment to Afghanistan in 2012. Latent growth mixture modeling was used to model posttraumatic stress symptom trajectories among participants who provided post-deployment data (n = 4353). Multinomial logistic regression models tested independent associations between trajectory membership and PRS for PTSD, major depressive disorder (MDD), schizophrenia, neuroticism, alcohol use disorder, and suicide attempt, controlling for age, sex, ancestry, and exposure to potentially traumatic events, and weighted to account for uncertainty in trajectory classification and missing data.

Participants were classified into low-severity (77.2%), increasing-severity (10.5%), decreasing-severity (8.0%), and high-severity (4.3%) posttraumatic stress symptom trajectories. Standardized PTSD-PRS and MDD-PRS were associated with greater odds of membership in the high-severity v. low-severity trajectory [adjusted odds ratios and 95% confidence intervals, 1.23 (1.06–1.43) and 1.18 (1.02–1.37), respectively] and the increasing-severity v. low-severity trajectory [1.12 (1.01–1.25) and 1.16 (1.04–1.28), respectively]. Additionally, MDD-PRS was associated with greater odds of membership in the decreasing-severity v. low-severity trajectory [1.16 (1.03–1.31)]. No other associations were statistically significant.

Higher polygenic risk for PTSD or MDD is associated with more severe posttraumatic stress symptom trajectories following combat deployment. PRS may help stratify at-risk individuals, enabling more precise targeting of treatment and prevention programs.

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Emotion reactivity and risk behaviors (ERRB) are transdiagnostic dimensions associated with suicide attempt (SA). ERRB patterns may identify individuals at increased risk of future SAs.

A representative sample of US Army soldiers entering basic combat training (n = 21 772) was surveyed and followed via administrative records for their first 48 months of service. Latent profile analysis of baseline survey items assessing ERRB dimensions, including emotion reactivity, impulsivity, and risk-taking behaviors, identified distinct response patterns (classes). SAs were identified using administrative medical records. A discrete-time survival framework was used to examine associations of ERRB classes with subsequent SA during the first 48 months of service, adjusting for time in service, socio-demographic and service-related variables, and mental health diagnosis (MH-Dx). We examined whether associations of ERRB classes with SA differed by year of service and for soldiers with and without a MH-Dx.

Of 21 772 respondents (86.2% male, 61.8% White non-Hispanic), 253 made a SA. Four ERRB classes were identified: ‘Indirect Harming’ (8.9% of soldiers), ‘Impulsive’ (19.3%), ‘Risk-Taking’ (16.3%), and ‘Low ERRB’ (55.6%). Compared to Low ERRB, Impulsive [OR 1.8 (95% CI 1.3–2.4)] and Risk-Taking [OR 1.6 (95% CI 1.1–2.2)] had higher odds of SA after adjusting for covariates. The ERRB class and MH-Dx interaction was non-significant. Within each class, SA risk varied across service time.

SA risk within the four identified ERRB classes varied across service time. Impulsive and Risk-Taking soldiers had increased risk of future SA. MH-Dx did not modify these associations, which may therefore help identify risk in those not yet receiving mental healthcare.

Personality traits (e.g. neuroticism) and the social environment predict risk for internalizing disorders and suicidal behavior. Studying these characteristics together and prospectively within a population confronted with high stressor exposure (e.g. U.S. Army soldiers) has not been done, yet could uncover unique and interactive predictive effects that may inform prevention and early intervention efforts.

Five broad personality traits and social network size were assessed via self-administered questionnaires among experienced soldiers preparing for deployment (N = 4645) and new soldiers reporting for basic training (N = 6216). Predictive models examined associations of baseline personality and social network variables with recent distress disorders or suicidal behaviors assessed 3- and 9-months post-deployment and approximately 5 years following enlistment.

Among the personality traits, elevated neuroticism was consistently associated with increased mental health risk following deployment. Small social networks were also associated with increased mental health risk following deployment, beyond the variance accounted for by personality. Limited support was found for social network size moderating the association between personality and mental health outcomes. Small social networks also predicted distress disorders and suicidal behavior 5 years following enlistment, whereas unique effects of personality traits on these more distal outcomes were rare.

Heightened neuroticism and small social networks predict a greater risk for negative mental health sequelae, especially following deployment. Social ties may mitigate adverse impacts of personality traits on psychopathology in some contexts. Early identification and targeted intervention for these distinct, modifiable factors may decrease the risk of distress disorders and suicidal behavior.

The transition from military service to civilian life is a high-risk period for suicide attempts (SAs). Although stressful life events (SLEs) faced by transitioning soldiers are thought to be implicated, systematic prospective evidence is lacking.

Participants in the Army Study to Assess Risk and Resilience in Servicemembers (STARRS) completed baseline self-report surveys while on active duty in 2011–2014. Two self-report follow-up Longitudinal Surveys (LS1: 2016–2018; LS2: 2018–2019) were subsequently administered to probability subsamples of these baseline respondents. As detailed in a previous report, a SA risk index based on survey, administrative, and geospatial data collected before separation/deactivation identified 15% of the LS respondents who had separated/deactivated as being high-risk for self-reported post-separation/deactivation SAs. The current report presents an investigation of the extent to which self-reported SLEs occurring in the 12 months before each LS survey might have mediated/modified the association between this SA risk index and post-separation/deactivation SAs.

The 15% of respondents identified as high-risk had a significantly elevated prevalence of some post-separation/deactivation SLEs. In addition, the associations of some SLEs with SAs were significantly stronger among predicted high-risk than lower-risk respondents. Demographic rate decomposition showed that 59.5% (s.e. = 10.2) of the overall association between the predicted high-risk index and subsequent SAs was linked to these SLEs.

It might be possible to prevent a substantial proportion of post-separation/deactivation SAs by providing high-risk soldiers with targeted preventive interventions for exposure/vulnerability to commonly occurring SLEs.

Problematic anger is frequently reported by soldiers who have deployed to combat zones. However, evidence is lacking with respect to how anger changes over a deployment cycle, and which factors prospectively influence change in anger among combat-deployed soldiers.

Reports of problematic anger were obtained from 7298 US Army soldiers who deployed to Afghanistan in 2012. A series of mixed-effects growth models estimated linear trajectories of anger over a period of 1–2 months before deployment to 9 months post-deployment, and evaluated the effects of pre-deployment factors (prior deployments and perceived resilience) on average levels and growth of problematic anger.

A model with random intercepts and slopes provided the best fit, indicating heterogeneity in soldiers' levels and trajectories of anger. First-time deployers reported the lowest anger overall, but the most growth in anger over time. Soldiers with multiple prior deployments displayed the highest anger overall, which remained relatively stable over time. Higher pre-deployment resilience was associated with lower reports of anger, but its protective effect diminished over time. First- and second-time deployers reporting low resilience displayed different anger trajectories (stable v. decreasing, respectively).

Change in anger from pre- to post-deployment varies based on pre-deployment factors. The observed differences in anger trajectories suggest that efforts to detect and reduce problematic anger should be tailored for first-time v. repeat deployers. Ongoing screening is needed even for soldiers reporting high resilience before deployment, as the protective effect of pre-deployment resilience on anger erodes over time.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Definition of disorder subtypes may facilitate precision treatment for posttraumatic stress disorder (PTSD). We aimed to identify PTSD subtypes and evaluate their associations with genetic risk factors, types of stress exposures, comorbidity, and course of PTSD.

Data came from a prospective study of three U.S. Army Brigade Combat Teams that deployed to Afghanistan in 2012. Soldiers with probable PTSD (PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition ≥31) at three months postdeployment comprised the sample (N = 423) for latent profile analysis using Gaussian mixture modeling and PTSD symptom ratings as indicators. PTSD profiles were compared on polygenic risk scores (derived from external genomewide association study summary statistics), experiences during deployment, comorbidity at three months postdeployment, and persistence of PTSD at nine months postdeployment.

Latent profile analysis revealed profiles characterized by prominent intrusions, avoidance, and hyperarousal (threat-reactivity profile; n = 129), anhedonia and negative affect (dysphoric profile; n = 195), and high levels of all PTSD symptoms (high-symptom profile; n = 99). The threat-reactivity profile had the most combat exposure and the least comorbidity. The dysphoric profile had the highest polygenic risk for major depression, and more personal life stress and co-occurring major depression than the threat-reactivity profile. The high-symptom profile had the highest rates of concurrent mental disorders and persistence of PTSD.

Genetic and trauma-related factors likely contribute to PTSD heterogeneity, which can be parsed into subtypes that differ in symptom expression, comorbidity, and course. Future studies should evaluate whether PTSD typology modifies treatment response and should clarify distinctions between the dysphoric profile and depressive disorders.

Unit cohesion may protect service member mental health by mitigating effects of combat exposure; however, questions remain about the origins of potential stress-buffering effects. We examined buffering effects associated with two forms of unit cohesion (peer-oriented horizontal cohesion and subordinate-leader vertical cohesion) defined as either individual-level or aggregated unit-level variables.

Longitudinal survey data from US Army soldiers who deployed to Afghanistan in 2012 were analyzed using mixed-effects regression. Models evaluated individual- and unit-level interaction effects of combat exposure and cohesion during deployment on symptoms of post-traumatic stress disorder (PTSD), depression, and suicidal ideation reported at 3 months post-deployment (model n's = 6684 to 6826). Given the small effective sample size (k = 89), the significance of unit-level interactions was evaluated at a 90% confidence level.

At the individual-level, buffering effects of horizontal cohesion were found for PTSD symptoms [B = −0.11, 95% CI (−0.18 to −0.04), p < 0.01] and depressive symptoms [B = −0.06, 95% CI (−0.10 to −0.01), p < 0.05]; while a buffering effect of vertical cohesion was observed for PTSD symptoms only [B = −0.03, 95% CI (−0.06 to −0.0001), p < 0.05]. At the unit-level, buffering effects of horizontal (but not vertical) cohesion were observed for PTSD symptoms [B = −0.91, 90% CI (−1.70 to −0.11), p = 0.06], depressive symptoms [B = −0.83, 90% CI (−1.24 to −0.41), p < 0.01], and suicidal ideation [B = −0.32, 90% CI (−0.62 to −0.01), p = 0.08].

Policies and interventions that enhance horizontal cohesion may protect combat-exposed units against post-deployment mental health problems. Efforts to support individual soldiers who report low levels of horizontal or vertical cohesion may also yield mental health benefits.