Pujan R. Patel

BACKGROUND: Recent investigations of the meninges have highlighted the importance of the dura layer in central nervous system immune surveillance beyond a purely structural role. However, our understanding of the meninges largely stems from the use of pre-clinical models rather than human samples. METHODS: Single-cell RNA sequencing of seven non-tumor-associated human dura samples and six primary meningioma tumor samples (4 matched and 2 non-matched) was performed. Cell type identities, gene expression profiles, and T cell receptor expression were analyzed. Copy number variant (CNV) analysis was performed to identify putative tumor cells and analyze intratumoral CNV heterogeneity. Immunohistochemistry and imaging mass cytometry was performed on selected samples to validate protein expression and reveal spatial localization of select protein markers. RESULTS: In this study, we use single-cell RNA sequencing to perform the first characterization of both non-tumor-associated human dura and primary meningioma samples. First, we reveal a complex immune microenvironment in human dura that is transcriptionally distinct from that of meningioma. In addition, we characterize a functionally diverse and heterogenous landscape of non-immune cells including endothelial cells and fibroblasts. Through imaging mass cytometry, we highlight the spatial relationship among immune cell types and vasculature in non-tumor-associated dura. Utilizing T cell receptor sequencing, we show significant TCR overlap between matched dura and meningioma samples. Finally, we report copy number variant heterogeneity within our meningioma samples. CONCLUSIONS: Our comprehensive investigation of both the immune and non-immune cellular landscapes of human dura and meningioma at single-cell resolution builds upon previously published data in murine models and provides new insight into previously uncharacterized roles of human dura.

Background: Suicidality, including suicidal ideation (SI), attempt (SA), and death (SD), represents complex and partially overlapping phenotypes. This complexity contributes to study population heterogeneity in suicidality research, impeding replication efforts and data consolidation by research consortia. The standardization of suicidality definitions would help but has been insufficiently addressed in existing literature. Here, the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) provides International Classification of Disease (ICD) definitions, a critical real-world data source, for SA and SI. Methods: The PGC Suicide Workgroup used published definitions coupled with expert consensus to develop ICD lists to serve as suicidality phenotype definitions. One SI and two SA lists were produced and evaluated for performance against patient screening responses in two independent cohorts (N = 9,151 and 12,621) with differing ascertainment strategies. Outcomes: ICD list suicidality definitions were produced. Evaluation of generated ICD lists versus patient responses across two cohorts demonstrated varied sensitivity (15·4% to 71·1%), specificity (67·6% to 96·3%), and positive predictive values (0·57-0·92). SI ICD code performance also varied in sensitivity (29·4%-86·1%), specificity (64·2% to 90·6%), and positive predictive values (0·67 to 0·98). Interpretation: Guidelines were developed to provide more consistent and comparable suicidality definitions. However, real-world application of ICD codes leads to a wide range of performance, dependent on cohort characteristics, that will need to be carefully considered in implementation. Future efforts would benefit from consistent training in use of ICD codes between sites to improve generalizability, and should include validation in diverse populations. Funding: This work was funded by NIMH R01MH132733 (Mullins), R01MH132733 (Ruderfer), R01MH123619 (Docherty), R01MH123489 (Coon), R01MH124839 (PGC4), R01MH118233 and MH117599 (Smoller), Brain and Behavior Research Foundation No. 31248 (Monson), the Huntsman Mental Health Institute, National Science Foundation Graduate Research Fellowship Program Grant #1842169, and by grant # I01BX005881 and #IK6BX006523 (Kimbrel) from the Department of Veterans Affairs.

Abstract Recent investigation of the meninges, specifically the dura layer, has highlighted its importance in CNS immune surveillance beyond a purely structural role. However, most of our understanding of the meninges stems from the use of pre-clinical models rather than human samples. In this study, we use single cell RNA-sequencing to perform the first characterization of both non-tumor-associated human dura and meningioma samples. First, we reveal a complex immune microenvironment in human dura that is transcriptionally distinct from that of meningioma. In addition, through T cell receptor sequencing, we show significant TCR overlap between matched dura and meningioma samples. We also identify a functionally heterogeneous population of non-immune cell types and report copy-number variant heterogeneity within our meningioma samples. Our comprehensive investigation of both the immune and non-immune cell landscapes of human dura and meningioma at a single cell resolution provide new insight into previously uncharacterized roles of human dura.

Many groups have reported lymphatic and glymphatic structures in animal and human brains, but tracer injection into the human brain to demonstrate real-time lymphatic drainage and mapping has not been described. We enrolled patients undergoing standard-of-care resection or stereotactic biopsy for suspected intracranial tumors. Patients received peritumoral injections of 99m Tc-tilmanocept followed by planar or tomographic imaging. Fourteen patients with suspected brain tumors were enrolled. One was excluded from analysis because of tracer leakage during injection. There was no drainage of 99m Tc-tilmanocept to regional lymph nodes in any of the patients. On average, after correcting for radioactive decay, 70.7% (95% CI: 59.9%, 81.6%) of the tracer in the injection site and 78.1% (95% CI: 71.1%, 85.1%) in the whole-head on the day of surgery remained the morning after, with variable radioactivity in the subarachnoid space. The retained fraction was much greater than expected based on the clearance rate from non-brain injection sites. In this pilot study, the lymphatic tracer 99m Tc-tilmanocept was injected into the brain parenchyma, and there was no drainage outside the brain to the cervical lymph nodes. Our work demonstrates an inefficiency of drainage from peritumoral brain parenchyma and highlights a therapeutic opportunity to improve immunosurveillance of the brain.

INTRODUCTION: Suicidality, including suicidal ideation (SI), attempt (SA), and death (SD), represents complex and partially overlapping phenotypes that are moderately heritable. Suicidality definition heterogeneity impedes data replication and consolidation efforts by research consortia needed to address the sample size requirements of genetic research. The standardization of suicidality definitions would improve comparability of data across groups but has been insufficiently addressed in existing literature. Here, the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) provides International Classification of Disease (ICD) definitions and validation in real-world data for SA and SI. METHODS: The PGC Suicide Workgroup used published definitions coupled with expert consensus to develop ICD lists to serve as suicidality phenotype definitions. One SI and two SA lists were produced and evaluated for performance, including via sex stratification, against patient screening responses in multiple independent cohorts (total N = 21,772) with differing ascertainment strategies. RESULTS: ICD code lists for suicidality component definitions were produced. SA ICD lists versus patient responses showed sensitivity of 15.4 % to 71.1 %, specificity of 67.6 % to 96.3 %, and positive predictive values of 0.57-0.92. SI ICD code performance versus patient report also varied in sensitivity (29.4 %-86.1 %), specificity (64.2 % to 90.6 %), and positive predictive values (0.67 to 0.98). CONCLUSIONS: Lists of applicable ICD codes for SI and SA were developed that complied with C-SSRS definitions. Real-world application of ICD codes can vary substantially, perhaps dependent on clinician training and on cohort characteristics. Consistent training in use of ICD codes between sites may improve comparability of data sets.