School of Medicine

Alopecia areata is thought to be a T-cell mediated and cytokine mediated autoimmune disease that results in non-scarring hair loss. Poliosis has been described as a localized depigmentation of hair caused by a deficiency of melanin in hair follicles. A 57-year-old man with a history of alopecia areata developed white hair regrowth in areas of previous hair loss. We retrospectively reviewed the medical literature using PubMed, searching: (1) alopecia areata and (2) poliosis. Poliosis may be associated with autoimmune diseases including alopecia areata, as described in our case. However, it is also reported in patients who have cutaneous lesions, genetic syndromes, infections, medication use, and trauma. Hair regrowth following alopecia areata may be associated with poliosis. We hypothesize that the incidence of poliosis in areas of previous alopecia areata-related hair loss may be greater than reflected in the published literature.

Glycation is a class of modifications arising from non-enzymatic reactions of reducing sugars with proteins, lipids, and/or DNA, generating advanced glycation end-products (AGEs). AGEs are linked to many age-related comorbidities. In response to HIV-1 infection, activated T-cells and macrophages shift their predominate metabolism from oxidative phosphorylation to glycolysis. Increased glycolytic flux enhances AGE formation, which may increase age-related comorbidities. In this prospective, multicenter cohort study of antiretroviral therapy treated people with HIV, we explored predictive associations by baseline plasma AGE concentrations and their corresponding detoxification metabolites, with incident comorbidities and mortality. AGEs included dicarbonyl sugars: 3-deoxyglucosone, glyoxal, and methylglyoxal. Methylglyoxal-derived metabolites included carboxyethyl-arginine, carboxyethyl-lysine, and methylglyoxal hydroimidazolone-1. Detoxification metabolites included reduced and oxidized glutathione, and the glyoxalase cycle products lactoyl-glutathione and lactoyl-Lysine modified proteins. Plasma was collected at study entry, in the fasting state, and assayed by liquid chromatography-mass spectroscopy. Incident clinical outcomes included diabetes, chronic kidney disease, hypertension, neurocognitive impairment, peripheral neuropathy, frailty, fractures, recurrent falls, and all-cause mortality. Among 376 participants, higher baseline plasma concentrations of methylglyoxal derived AGEs predicted increased risks of diabetes, chronic kidney disease, and recurrent falls, while higher 3-deoxyglucosone predicted an increased risk of peripheral neuropathy. By contrast, higher baseline concentrations of reduced or oxidized glutathione, lactoyl-glutathione, and/or lactoyl-Lysine modified proteins predicted lower risks of diabetes, neurocognitive impairment, frailty, fractures, recurrent falls, and all-cause mortality. These findings support growing experimental evidence of the potential to mitigate age-related declines by interventions that reduce glycation or increase glutathione.

Clinical ascertainment and clinical outcome are key features of any large multisite study. In the ProNET and PRESCIENT research networks, the Accelerating Medicines Partnership® Schizophrenia (AMP®SCZ) Clinical Ascertainment and Outcome Measures Team aimed to establish a harmonized clinical assessment protocol across these two research networks and to define ascertainment criteria and primary and secondary endpoints. In addition to developing the assessment protocol, the goals of this aspect of the AMP SCZ project were: (1) to implement and monitor clinical training, ascertainment of participants, and clinical assessments; (2) to provide expert clinical input to the Psychosis Risk Evaluation, Data Integration and Computational Technologies: Data Processing, Analysis, and Coordination Center (PREDICT-DPACC) for data collection, quality control, and preparation of data for the analysis of the clinical measures; and (3) to provide ongoing support to the collection, analysis, and reporting of clinical data. This paper describes the (1) protocol clinical endpoints and outcomes, (2) rationale for the selection of the clinical measures, (3) extensive training of clinical staff, (4) preparation of clinical measures for a multisite study which includes several sites where English is not the native language; and (5) the assessment of measure stability over time in the AMP SCZ observational study comparing clinical ratings at baseline and at the 2-month follow up. Watch Dr. Jean Addington discuss her work and this article: https://vimeo.com/1040425281 .

Neuroimaging with MRI has been a frequent component of studies of individuals at clinical high risk (CHR) for developing psychosis, with goals of understanding potential brain regions and systems impacted in the CHR state and identifying prognostic or predictive biomarkers that can enhance our ability to forecast clinical outcomes. To date, most studies involving MRI in CHR are likely not sufficiently powered to generate robust and generalizable neuroimaging results. Here, we describe the prospective, advanced, and modern neuroimaging protocol that was implemented in a complex multi-site, multi-vendor environment, as part of the large-scale Accelerating Medicines Partnership® Schizophrenia Program (AMP® SCZ), including the rationale for various choices. This protocol includes T1- and T2-weighted structural scans, resting-state fMRI, and diffusion-weighted imaging collected at two time points, approximately 2 months apart. We also present preliminary variance component analyses of several measures, such as signal- and contrast-to-noise ratio (SNR/CNR) and spatial smoothness, to provide quantitative data on the relative percentages of participant, site, and platform (i.e., scanner model) variance. Site-related variance is generally small (typically <10%). For the SNR/CNR measures from the structural and fMRI scans, participant variance is the largest component (as desired; 40-76%). However, for SNR/CNR in the diffusion scans, there is substantial platform-related variance (>55%) due to differences in the diffusion imaging hardware capabilities of the different scanners. Also, spatial smoothness generally has a large platform-related variance due to inherent, difficult to control, differences between vendors in their acquisitions and reconstructions. These results illustrate some of the factors that will need to be considered in analyses of the AMP SCZ neuroimaging data, which will be the largest CHR cohort to date.Watch Dr. Harms discuss this article at https://vimeo.com/1059777228?share=copy#t=0 .

Public safety personnel (PSP), such as police officers, firefighters, correctional workers, and paramedics, routinely face work stressors that increase their risk of developing posttraumatic stress disorder (PTSD). PSP may additionally face moral transgressions in the workplace (e.g., witnessing human suffering, working within broken systems), heightening the risk of moral injury (MI) in this population. Research among military personnel and health care workers shows an association between MI and PTSD; however, less is known about the association between these constructs among PSP. Canadian PSP completed an online survey between June 2022 and June 2023, including a demographic questionnaire and measures of PTSD, MI, dissociation, depression, anxiety, stress, and childhood adversity. Latent variable structural equation modeling (SEM) was performed to ascertain the impact of a latent MI construct (i.e., shame, trust violation, functional impairment) on a latent PTSD construct (i.e., intrusions, avoidance, negative alterations in cognition and mood, hyperreactivity, depersonalization, derealization). Sex, age, depression, anxiety, stress, and childhood adversity were included as covariates. A total of 314 PSP were included in the data analysis. A latent variable SEM regressing PTSD onto MI and including covariates accounted for 83.7% of the variance in PTSD. MI was the strongest predictor compared to all covariates and was significantly associated with PTSD symptoms, β = .506, p < .001, above and beyond the impacts of sex, age, depression, anxiety, stress, and childhood adversity. These findings are consistent with research among military members and health care providers and highlight the importance of further exploring MI among PSP.

With the many negative health consequences of cigarette smoking, quitting is known to improve health in multiple domains. Using positron emission tomography/computed tomography (PET/CT) scanning, our group previously demonstrated that smokers have lower levels than nonsmokers of translocator protein binding both acutely and following overnight abstinence. Here, we sought to determine the effects of longer smoking abstinence on this marker of gliosis for microglia and astroglia, as well as explore associations between the marker and smoking-related symptoms. This observational study was performed in an academic VA medical centre. Fifty-nine generally healthy Veterans who were either nonsmokers (n = 15) or smokers (n = 44) participated in the study. Participants completed an intake visit to evaluate for inclusion/exclusion criteria, [¹⁸F]FEPPA PET/CT scanning and a structural magnetic resonance imaging scan. Smokers were alternately assigned either to smoke to satiety (n = 24) before scanning or undergo three nights of continuous abstinence prior to scanning using contingency management (n = 20 completed this protocol and scanning). The smoker satiety group had a significantly lower mean whole brain (WB) standardized uptake value (SUV) for [¹⁸F]FEPPA binding than both the nonsmoking (-15.3%) and abstinent smoker (-12.3%) groups. The nonsmoking control and abstinent smoker groups had mean WB SUVs that were not significantly different from one another (3.0% group difference). In an exploratory analysis, a significant inverse relationship was found between WB SUVs and mood ratings for smokers, indicating that higher levels of TSPO binding were associated with worse mood. The central findings here support previous studies demonstrating lower levels of the marker for gliosis in satiated smokers and imply normalization with elimination of cigarette smoke constituents from the body, although other explanations for study results (e.g., alterations in radioligand delivery or clearance of radioligand by cigarette smoke constituents) are possible. These findings may represent a previously unknown health benefit of quitting smoking.

This editorial focuses on the issue of data misuse which is increasingly evidenced in social media as well as some premiere scientific journals. This issue is of critical importance to open science projects in general, and ABCD in particular, given the broad array of biological, behavioral and environmental information collected on this American sample of 12.000 youth and parents. ABCD data are already widely used with over 1000 publications and twice as many citations per year as expected (relative citation index based on year, field and journal). However, the adverse consequences of misuse of data, and inaccurate interpretation of emergent findings from this precedent setting study may have profound impact on disadvantaged populations and perpetuate biases and societal injustices.