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Post-traumatic stress disorder (PTSD) is a mental disorder diagnosed by clinical interviews, self-report measures and neuropsychological testing. Traumatic brain injury (TBI) can have neuropsychiatric symptoms similar to PTSD. Diagnosing PTSD and TBI is challenging and more so for providers lacking specialized training facing time pressures in primary care and other general medical settings. Diagnosis relies heavily on patient self-report and patients frequently under-report or over-report their symptoms due to stigma or seeking compensation. We aimed to create objective diagnostic screening tests utilizing Clinical Laboratory Improvement Amendments (CLIA) blood tests available in most clinical settings. CLIA blood test results were ascertained in 475 male veterans with and without PTSD and TBI following warzone exposure in Iraq or Afghanistan. Using random forest (RF) methods, four classification models were derived to predict PTSD and TBI status. CLIA features were selected utilizing a stepwise forward variable selection RF procedure. The AUC, accuracy, sensitivity, and specificity were 0.730, 0.706, 0.659, and 0.715, respectively for differentiating PTSD and healthy controls (HC), 0.704, 0.677, 0.671, and 0.681 for TBI vs. HC, 0.739, 0.742, 0.635, and 0.766 for PTSD comorbid with TBI vs HC, and 0.726, 0.723, 0.636, and 0.747 for PTSD vs. TBI. Comorbid alcohol abuse, major depressive disorder, and BMI are not confounders in these RF models. Markers of glucose metabolism and inflammation are among the most significant CLIA features in our models. Routine CLIA blood tests have the potential for discriminating PTSD and TBI cases from healthy controls and from each other. These findings hold promise for the development of accessible and low-cost biomarker tests as screening measures for PTSD and TBI in primary care and specialty settings.

We sought to find clinical subtypes of posttraumatic stress disorder (PTSD) in veterans 6–10 years post-trauma exposure based on current symptom assessments and to examine whether blood biomarkers could differentiate them. Samples were males deployed to Iraq and Afghanistan studied by the PTSD Systems Biology Consortium: a discovery sample of 74 PTSD cases and 71 healthy controls (HC), and a validation sample of 26 PTSD cases and 36 HC. A machine learning method, random forests (RF), in conjunction with a clustering method, partitioning around medoids, were used to identify subtypes derived from 16 self-report and clinician assessment scales, including the clinician-administered PTSD scale for DSM-IV (CAPS). Two subtypes were identified, designated S1 and S2, differing on mean current CAPS total scores: S2 = 75.6 (sd 14.6) and S1 = 54.3 (sd 6.6). S2 had greater symptom severity scores than both S1 and HC on all scale items. The mean first principal component score derived from clinical summary scales was three times higher in S2 than in S1. Distinct RFs were grown to classify S1 and S2 vs. HCs and vs. each other on multi-omic blood markers feature classes of current medical comorbidities, neurocognitive functioning, demographics, pre-military trauma, and psychiatric history. Among these classes, in each RF intergroup comparison of S1, S2, and HC, multi-omic biomarkers yielded the highest AUC-ROCs (0.819–0.922); other classes added little to further discrimination of the subtypes. Among the top five biomarkers in each of these RFs were methylation, micro RNA, and lactate markers, suggesting their biological role in symptom severity.

Neuroimaging-based subtyping is increasingly used to explain heterogeneity in psychiatric disorders. However, the clinical utility of these subtyping efforts remains unclear, and replication has been challenging. Here we examined how the choice of neuroimaging measures influences the derivation of neuro-subtypes and the consequences for clinical delineation. On a clinically heterogeneous dataset (total n  = 566) that included controls ( n  = 268) and cases ( n  = 298) of psychiatric conditions, including individuals diagnosed with post-traumatic stress disorder (PTSD), traumatic brain injury (TBI), and comorbidity of both (PTSD&TBI), we identified neuro-subtypes among the cases using either structural, resting-state, or task-based measures. The neuro-subtypes for each modality had high internal validity but did not significantly differ in their clinical and cognitive profiles. We further show that the choice of neuroimaging measures for subtyping substantially impacts the identification of neuro-subtypes, leading to low concordance across subtyping solutions. Similar variability in neuro-subtyping was found in an independent dataset ( n  = 1642) comprised of major depression disorder (MDD, n  = 848) and controls ( n  = 794). Our results suggest that the highly anticipated relationships between neuro-subtypes and clinical features may be difficult to discover.

Existing New York City data were used to examine the correlation of residential area-level measures of poverty, race, and ethnicity with rates of buprenorphine and methadone treatment use. The hypothesis tested is that methadone treatment rates are the highest in the residential areas with the lowest incomes and highest percentages of black and Hispanic residents, while buprenorphine treatment rates are the highest in the residential areas with the highest incomes and lowest percentages of black and Hispanic residents.

Objectives. We sought to estimate the extended mental health service capacity requirements of persons affected by the September 11, 2001, terrorist attacks. Methods. We developed a formula to estimate the extended mental health service capacity requirements following disaster situations and assessed availability of the information required by the formula. Results. Sparse data exist on current services and supports used by people with mental health problems outside of the formal mental health specialty sector. There also are few systematically collected data on mental health sequelae of disasters. Conclusions. We recommend research-based surveys to understand service usage in non–mental health settings and suggest that federal guidelines be established to promote uniform data collection of a core set of items in studies carried out after disasters.

The NKI Cultural Competency Assessment Scale measures organizational CC in mental health outpatient settings. We describe its development and results of tests of its psychometric properties. When tested in 27 public mental health settings, factor analysis discerned three factors explaining 65% of the variance; each factor related to a stage of implementation of CC. Construct validity and inter-rater reliability were satisfactory. In tests of predictive validity, higher scores on items related to linguistic and service accommodations predicted a reduction in service disparities for engagement and retention outcomes for Hispanics. Disparities for Blacks essentially persisted independent of CC scores.

Long-term risks of gene therapy are not fully understood. In this study, we evaluated safety outcomes in 783 patients over more than 2,200 total patient-years of observation from 38 T cell therapy trials. The trials employed integrating gammaretroviral or lentiviral vectors to deliver engineered receptors to target HIV-1 infection or cancer. Eighteen patients (2.3%) developed secondary malignancies after treatment, with a median onset of 1.94 years (range: 51 d to 14 years). Where possible, incident tumor samples were analyzed for vector copy number, revealing no evidence of high-level marking or other indications of insertional mutagenesis. One T cell lymphoma was detected, but malignant T cells were not marked by vector integration. Analysis of vector integration sites in 176 patients revealed no pathological insertions linked to secondary malignancies, although, in some cases, integration in or near specific genes, including tumor suppressor genes, was associated with modest clonal expansion and sustained T cell persistence. These findings highlight the safety of engineered T cell therapies. In an analysis of long-term safety events in 783 patients treated with T cell therapy in 38 trials, 2.3% of patients developed second primary malignancies, and vector integration analyses revealed no pathological insertions.

Adolescent obesity continues to be a major public health issue with a third of American adolescents being overweight or obese. Excess weight is associated with cardiovascular risk factors and pre-diabetes. High school students identified as carrying excess weight [body mass index (BMI) ≥25 kg/m², or BMI percentile C85 %] were invited to participate in The BODY Project, an intervention that included a medical evaluation and a personalized medical report of the results of that evaluation sent to the parent/guardian at home. The medical evaluation and report was repeated 12 months later. The reports also contained advice on how the individual student could modify their lifestyle to improve the specific medical parameters showing abnormalities. Outcomes were change in BMI, blood pressure, high-density lipoprotein (HDL), lowdensity lipoprotein (LDL), fasting glucose, and fasting insulin. Students participating in The BODY Project intervention demonstrated modest, yet significant, reductions in BMI (p < 0.001) 1 year later, and also had significant improvements in systolic blood pressure (p < 0.001) and cholesterol profile (HDL p = 0.002; LDL p < 0.001) at follow-up. The BODY Project, by means of a minimal educational program anchored on the principle of teachable moments around the students’increased perception of their own risk for disease from the medical abnormalities uncovered, demonstrates evidence of potential effectiveness in addressing adolescent obesity.

Current statistical designs for studying whether two or more agents in combination act synergistically nearly always require the study of several doses of many dose ratios. The analysis is usually based on an assumed parametric model of the dose-response surface. In this paper, for both quantal and quantitative response variables, sufficient conditions are given for establishing synergy at a dose of the combination without the need to specify the model. This enables the use of simple designs with few doses even when there is sparse knowledge of the dose-response curves of the individual agents. The Min test, used for testing whether an identified treatment is best, may be used for testing synergy. Power issues are discussed.