We endeavored to identify objective blood biomarkers for pain, a subjective sensation with a biological basis, using a stepwise discovery, prioritization, validation, and testing in independent cohorts design. We studied psychiatric patients, a high risk group for co-morbid pain disorders and increased perception of pain. For discovery, we used a powerful within-subject longitudinal design. We were successful in identifying blood gene expression biomarkers that were predictive of pain state, and of future emergency department (ED) visits for pain, more so when personalized by gender and diagnosis. MFAP3, which had no prior evidence in the literature for involvement in pain, had the most robust empirical evidence from our discovery and validation steps, and was a strong predictor for pain in the independent cohorts, particularly in females and males with PTSD. Other biomarkers with best overall convergent functional evidence for involvement in pain were GNG7, CNTN1, LY9, CCDC144B, and GBP1. Some of the individual biomarkers identified are targets of existing drugs. Moreover, the biomarker gene expression signatures were used for bioinformatic drug repurposing analyses, yielding leads for possible new drug candidates such as SC-560 (an NSAID), and amoxapine (an antidepressant), as well as natural compounds such as pyridoxine (vitamin B6), cyanocobalamin (vitamin B12), and apigenin (a plant flavonoid). Our work may help mitigate the diagnostic and treatment dilemmas that have contributed to the current opioid epidemic.

The Major Histocompatibility Complex (MHC) Class II Transactivator (CIITA) mediates activated immune responses and its deficiency results in the Type II Bare Lymphocyte Syndrome. CIITA is a transcriptional co-activator that regulates γ-interferon-activated transcription of MHC class I and class II genes. It is also a functional homolog of TAF1, a component of the general transcription factor complex TFIID. TAF1 and CIITA both possess intrinsic acetyltransferase (AT) activity that is required for transcription initiation. In response to induction by γ-Interferon, CIITA and it’s AT activity bypass the requirement for TAF1 AT activity. TAF1 also has kinase activity that is essential for its function. However, no similar activity has been identified for CIITA thus far. Here we report that CIITA, like TAF1, is a serine-threonine kinase. Its substrate specificity parallels, but does not duplicate, that of TAF1 in phosphorylating the TFIID component TAF7, the RAP74 subunit of the general transcription factor TFIIF and histone H2B. Like TAF1, CIITA autophosphorylates, affecting its interaction with TAF7. Additionally, CIITA phosphorylates histone H2B at Ser36, a target of TAF1 that is required for transcription during cell cycle progression and stress response. However, unlike TAF1, CIITA also phosphorylates all the other histones. The identification of this novel kinase activity of CIITA further clarifies its role as a functional homolog of TAF1 which may operate during stress and γ-IFN activated MHC gene transcription.

Purpose The novel Coronavirus Disease 19 (COVID-19) has had a significant impact worldwide that led to changes in healthcare. The purpose of this study was to evaluate the effect of the COVID-19 pandemic on trainee’s mental health and educational preparedness. Methods Trainees at the Indiana University School of Medicine were surveyed regarding the impact of the COVID-19 pandemic on their training. Using a Likert scale, participants were asked questions pertaining to educational preparedness, mental health, and clinical work during the pandemic. Data was analyzed using SPSS version 27. The study was approved as exempt by the Institutional review Board (IRB). Results 324 of the 1204 trainees responded to the survey. The respondents were 76% white with an equal distribution of males and females. A majority of the respondents were first year residents with an equal distribution of second, third, and fourth year residents. Twenty-three percent of respondents were in a procedural residency or fellowship program. Better perceived educational preparedness was associated with an improved home-work balance during COVID-19 (β = 0.506, p < 0.0001) and having a department that advocated/supported focus on mental health during COVID-19 (β = 0.177, p < 0.0001). Worse perceived educational preparedness was associated with being in procedural vs. non-procedural dominant training program (β = − 0.122, p = 0.01). Conclusion COVID-19 has had a significant impact on the training experience of residents and fellows. Departmental support increased mental well-being and perceived education preparedness in trainees. Trainees that felt they had a better home-work life balance had better educational preparedness compared to their peers. Also, trainees in procedural programs had less educational preparedness compared to their peers in non-procedural programs. This study highlights the importance for programs to find avenues to increase educational preparedness in their trainees while being attuned to the mental health of their trainees.

Anxiety disorders are increasingly prevalent, affect people’s ability to do things, and decrease quality of life. Due to lack of objective tests, they are underdiagnosed and sub-optimally treated, resulting in adverse life events and/or addictions. We endeavored to discover blood biomarkers for anxiety, using a four-step approach. First, we used a longitudinal within-subject design in individuals with psychiatric disorders to discover blood gene expression changes between self-reported low anxiety and high anxiety states. Second, we prioritized the list of candidate biomarkers with a Convergent Functional Genomics approach using other evidence in the field. Third, we validated our top biomarkers from discovery and prioritization in an independent cohort of psychiatric subjects with clinically severe anxiety. Fourth, we tested these candidate biomarkers for clinical utility, i.e. ability to predict anxiety severity state, and future clinical worsening (hospitalizations with anxiety as a contributory cause), in another independent cohort of psychiatric subjects. We showed increased accuracy of individual biomarkers with a personalized approach, by gender and diagnosis, particularly in women. The biomarkers with the best overall evidence were GAD1, NTRK3, ADRA2A, FZD10, GRK4, and SLC6A4. Finally, we identified which of our biomarkers are targets of existing drugs (such as a valproate, omega-3 fatty acids, fluoxetine, lithium, sertraline, benzodiazepines, and ketamine), and thus can be used to match patients to medications and measure response to treatment. We also used our biomarker gene expression signature to identify drugs that could be repurposed for treating anxiety, such as estradiol, pirenperone, loperamide, and disopyramide. Given the detrimental impact of untreated anxiety, the current lack of objective measures to guide treatment, and the addiction potential of existing benzodiazepines-based anxiety medications, there is a urgent need for more precise and personalized approaches like the one we developed.