Citations

ABSTRACT Suicidality contributes substantially to global morbidity and mortality, yet despite its heritability, its biological etiology remains largely elusive. We conducted multi-ancestry genome-wide association study meta-analyses of suicidal ideation (259,747 cases), suicide attempt (64,993 cases), suicide death (9,197 cases), and suicidal behavior (suicide attempt/ death, 75,300 cases), across 54 cohorts (e.g., the Psychiatric Genomics Consortium, Million Veteran Program, UK Biobank). We identified 77 significant loci across meta-analyses, including 59 previously unreported for suicidality. SNP-based heritability ranged from 2.0-6.7% and there were strong, yet incomplete, genetic correlations between suicidality phenotypes (0.70-0.88). Fine-mapping prioritized putative causal SNPs and 20 credible genes. Enrichment analyses implicated synaptic pathways and neuronal populations predominantly in subcortical brain regions (e.g., amygdala excitatory, medium spiny, hippocampal CA1-3). Together, these findings establish suicidality as a polygenic set of traits with both shared and distinct genetic influences, providing a foundation for future studies of suicide biology and etiology.

Background Challenges in predicting which neoantigens mediate tumor rejection limit the efficacy of neoantigen vaccines to treat cancers, especially for cancers with a high mutational burden like cutaneous squamous cell carcinoma (cSCC). Only a small portion of neoantigens prioritized by current methods elicit effective T cell responses, demonstrating the critical need for improved criteria for the prediction of tumor-rejecting neoantigens. Methods Publicly available human cSCC datasets were used to assess the frequency of shared mutations between patients. A transplantable ultraviolet light-induced mouse model of cSCC was generated. The mutational signature and driver mutations in the mouse model were compared with human tumors. Neoantigens were prioritized in the mouse model, and tumor-rejecting neoantigens were identified through (enzyme-linked immunosorbent spot (ELISpot) and in vivo prophylactic vaccination. Binding of the neoantigens and corresponding wild-type peptides to major histocompatibility complex (MHC) class I was determined. Structural modeling of peptide:MHC complexes was performed to assess for changes in structural characteristics of the neoantigens relative to the wild-type peptides. Results A minority of human cSCC tumors shared neoantigens. The mouse cSCC model recapitulated the mutational signature and driver mutations found in human disease and was constrained by CD8 T cells. Two MHC class I neoantigens were identified in the mouse model that constrained cSCC growth. One tumor-rejecting neoantigen exhibited improved MHC binding, and the other had increased solvent accessibility of the mutated residue, compared with wild-type. Across known neoantigens that do not impact MHC binding, increased exposure of the mutated residue distinguished tumor-rejecting from non-immunogenic neoantigens. Conclusions Given the paucity of shared mutations, this work supports the need for personalized neoantigen vaccines in cSCC. To facilitate further discovery, we provide a clinically relevant mouse cSCC model with two defined neoantigens that mediate tumor rejection. Structural changes in the exposure of features that promote T cell receptor recognition defined tumor-rejecting neoantigens. Incorporation of structural modeling to predict changes in T cell receptor accessibility is anticipated to improve the selection of neoantigens for inclusion in personalized cancer vaccines.

Abstract Background Rh immune globulin (RhIG) is used to prevent D alloimmunization and reduce the risk of hemolytic disease of the fetus and newborn (HDFN). Its use has been expanded to include immunoprophylaxis after D‐incompatible transfusions. In the United States, a protracted RhIG shortage began in 2023. The AABB (Association for the Advancement of Blood & Biotherapies) Clinical Hemotherapy Subsection created a survey to assess RhIG usage patterns during this shortage. Methods A survey was developed and electronically distributed to AABB‐accredited institutions. The number of responses was tallied. Frequencies were calculated, and free text comments were categorized. Results A total of 112 responses (13.7%) were received from all regions of the United States. While 6.2% (6/97) of respondents noticed increased RhIG usage, 70.0% (56/80) experienced a shortage of RhIG. The most common indication reported for RhIG use was D‐negative pregnant patients carrying a D‐unknown or D‐positive fetus/neonate. Some respondents also permitted RhIG use in D‐negative adult males and females outside of childbearing age following D‐incompatible transfusion. The most common institutional responses to the shortage were to: formally monitor RhIG inventory ( n = 37), add ( n = 34)/switch ( n = 24) manufacturers, and redistribute RhIG between facilities ( n = 22). Few respondents ( n = 7) limited or discontinued RhIG use in non‐obstetric patients. Conclusions While the majority of survey respondents were affected by the RhIG shortage, transfusion services still allowed RhIG to be issued outside of obstetric care. Given that RhIG is a limited resource and its intended goal is to reduce anti‐D HDFN, more effective management of RhIG utilization is needed.

Immune checkpoint inhibitors (ICIs) are an important class of cancer treatment. Endocrine immune-related adverse events (E-irAEs) account for a significant proportion of irAEs in ICI-treated patients. Diagnosing E-irAEs accurately and timely can be challenging in the absence of clear categorization and standardization across oncology, endocrinology and other specialties. While existing guidelines provide some broad directions to diagnosis and management, they lack clarity on irAE-specific symptom evaluation and work-up, as well as assessment of severity. These limitations can then impact triage, time-sensitive management and care escalation to specialists such as oncoendocrinologists. The objective of this study was to develop consensus-based statements on disease definitions for E-irAEs. A core working group of endocrinologists with expertise in the oncoendocrinology field drafted a survey with statements outlining the general approach to E-irAEs, disease definition and management approach of six specific diagnoses: ir-thyroiditis thyrotoxic phase, ir-thyroiditis hypothyroidism, ir-Graves’ disease, ir-hypophysitis, ir-adrenalitis and ir-type 1 diabetes mellitus. Severity grading tables were drafted for three disease categories—“thyroid”, “pituitary and adrenal”, and “diabetes mellitus”. A two-round modified Delphi process, using the RAND/University of California Los Angeles (RAND/UCLA) Appropriateness Method, was employed. In this process, a 25-member voting panel consisting of endocrinologists, oncologists and other specialists and healthcare providers with experience in management of ICI-treated patients and irAEs was recruited. The panel rated anonymously on usability, accuracy, appropriateness or agreement of 41 items on a 9-point scale in Survey 1, after which a meeting was convened. Statements were modified based on voting results from Survey 1 and Meeting 1, and the process was repeated in Survey 2 and Meeting 2. At the end of this process, consensus was achieved for all statements. Our study findings address the gap in standardized nomenclature, clinical, laboratory and radiological evaluations, and management principles of E-irAEs. With consensus achieved from a panel of experts from a variety of disciplines, we anticipate that the statements can form the basis for standardization of the diagnostic process and improvement of patient care.

Abstract Our understanding of Alzheimer's disease (AD) and related dementias (ADRD) has grown exponentially, thanks to significant investments by the National Institute on Aging (NIA). This article celebrates the 40th anniversary of the NIA's Alzheimer's Disease Research Centers, highlighting the pivotal role of neuropathology as the bedrock for neurodegeneration research. Neuropathology has championed the key principles of proteinopathy, selective vulnerability, and stereotypic spread. Furthermore, neuropathologic studies advanced our understanding of ADRD prevalence, heterogeneity, clinical–pathological correlations, and genetic underpinnings, spurring biomarker development for target engagement and disease monitoring. Disease‐modifying therapies for AD were inspired and informed by neuropathology. The neuropathology community is poised to refine diagnostics, leveraging digital pathology and integrating genetics and pathomics to enhance subtyping for novel precision medicine approaches. Despite some common misconceptions and logistical challenges, neuropathology continues to be a critical component of the ADRD research infrastructure, serving as a key bridge between allied basic and clinical sciences. Highlights We celebrate 40 years of NIA‐funded ADRCs and their contributions through neuropathology studies that have significantly advanced our understanding and treatment of ADRD. Neuropathology uncovers principles of neurodegenerative disease: proteinopathy, selective vulnerability, and stereotypic spread, informing diagnostics and therapies. Development of AD biomarkers with reference to neuropathology enhances accuracy in diagnosis and monitoring, paving the way for targeted disease‐modifying therapies. Integration of digital pathology, genetics, and novel tools in neurodegeneration research promises advanced precision medicine approaches and refined diagnostics. Misconceptions and logistical challenges to neuropathological research are addressed to improve understanding and collaboration.

PURPOSE Recent studies reveal that 5%-18% of children with cancer harbor pathogenic variants in known cancer-predisposing genes. However, DNA damage repair (DDR) genes, which are frequently somatically altered in pediatric tumors, have not been systematically examined as a source of novel cancer-predisposing signals. METHODS To address this gap, we interrogated 189 DDR genes for presence of germline predisposing variants (PV) among 5,993 childhood cancer cases and 14,477 adult noncancer controls (discovery cohort). PV were determined using a tiered approach incorporating ClinVar annotations, InterVar classification, and in silico tools (REVEL, CADD, and MetaSVM). Using logistic and firth regression, we identified genes with PV statistically enriched in the germline of children with tumors and replicated findings among 1,497 additional childhood cancer cases across three independent cohorts. RESULTS Analysis across all cases with cancer revealed enrichment of TP53 PV. Cancer-specific analyses confirmed known associations including germline TP53 PV in adrenocortical carcinoma, high-grade glioma (HGG), and medulloblastoma (MB), PMS2 in HGG and non-Hodgkin lymphoma (NHL), MLH1 in HGG, BRCA2 in NHL, and BARD1 in neuroblastoma. In addition, four novel associations were uncovered, including BRCA1 in ependymoma, SPIDR in HGG, SMC5 in MB, and SMARCAL1 in osteosarcoma (OS). Importantly, the SMARCAL1 :OS association was significant in the discovery (6/230, 2.6%, false discovery rate [FDR] logistic = 0.0189) as well as all three replication cohorts (Childhood Cancer Survivor Study: 8/275, 2.9%; P Fisher < .0001; Cancer Predisposition Syndrome-German Childhood Cancer Registry: 4/135, 3%, P Fisher = .002; Individualized Therapy for Relapsed Malignancies in Childhood: 4/217, 1.8%, P Fisher = .012). The remaining wild-type SMARCAL1 allele was deleted in three of four OS tumors with available data. CONCLUSION Our study confirms the relevance DDR genetic variation in pediatric cancer risk and establishes SMARCAL1 as a novel OS predisposing gene, providing insights into tumor biology and creating opportunities to optimize care for patients with this challenging tumor.

Abstract Aberrant DNA methylation and copy-number alterations (CNA) drive Barrett’s esophagus progression to esophageal adenocarcinoma; however, their combined utility for early detection is unclear. We aimed to identify and validate methylated DNA markers (MDM) and CNAs to distinguish esophageal adenocarcinoma/high-grade dysplasia (HGD) from nondysplastic Barrett’s esophagus (NDBE). In this multiphase, multicenter study, we discovered and validated MDMs and quantified CNAs utilizing whole-genome methylation sequencing of esophageal brushings. DNA biomarkers identified from discovery were further validated in independent patients with paired esophageal brushing and swallowed capsule sponge samples. MDMs were filtered against a reduced representation bisulfite sequencing dataset obtained from independent tissue samples to advance only concordant candidates. CNA burden was quantified using ichorCNA-derived aneuploidy scores (AS). Two hundred MDMs discovered in HGD (N = 18) and esophageal adenocarcinoma (N = 18) versus NDBE brushing samples (N = 18) were tested in independent samples (N = 146). A 52-MDM panel achieved a cross-validated AUC of 0.88 [95% confidence interval (CI), 0.82–0.95]; the addition of AS improved discrimination of HGD/esophageal adenocarcinoma from NDBE to 0.91 (95% CI, 0.86–0.97) AUC. At 80% specificity, the combined model detected 93% of esophageal adenocarcinoma and 88% of HGD cases. In paired capsule sponge samples, a 58-MDM panel achieved a cross-validated AUC of 0.77 (95% CI, 0.66–0.88); a combined 58-MDM and AS model achieved AUC 0.80 (95% CI, 0.7–0.9). MDMs and AS discerned HGD/esophageal adenocarcinoma from normal esophagus/NDBE in endoscopic brushing and capsule sponge samples. This approach may improve Barrett’s esophagus surveillance. Prevention Relevance: This study demonstrates that combining epigenetic and genomic biomarkers across minimally invasive sampling methods can accurately distinguish HGD/esophageal adenocarcinoma from nondysplastic Barrett’s esophagus, offering promising, less invasive strategies to improve BE surveillance and enable endoscopic therapy for esophageal adenocarcinoma prevention and treatment.

Abstract INTRODUCTION Few African American (AA) donors have been included in post mortem Alzheimer's disease (AD) studies compared to European‐ancestry (EA) individuals. METHODS We generated transcriptome‐wide bulk pre‐frontal cortex (PFC) gene expression data from 125 AA donors with neuropathologically determined AD and 82 AA controls. RESULTS Transcriptome‐wide significant differential expression was observed with 482 genes. The most significant, ADAMTS2 , showed 1.52 times higher expression in AD cases ( p = 2.96x10 −8 ). Comparison of findings with those from a recent gene expression study of EA brain donors revealed substantial concordance, including ADAMTS2 . Other associations not observed in EA results may be especially relevant to AD risk in the AA population. Examination of AA AD GWAS‐implicated variants identified several expression quantitative trait loci. CONCLUSION This first large‐scale AA brain AD gene expression study identified many differentially expressed genes, including ADAMTS2 , and supports gene expression as a molecular pathway underlying the impact of several AA AD risk variants. Highlights We performed the largest African American brain tissue Alzheimer's disease (AD) gene expression study. Expression differences for 482 genes, notably ADAMTS2 , were study‐wide significant. Many significant differentially expressed genes are involved in energy metabolism. Several previously known AD‐associated variants in African Americans are eQTLs. These results advance knowledge of the genetic basis of AD in the AA population.

Abstract Background Anti-citrullinated peptide antibodies (ACPA) (tested as anti-cyclic citrullinated peptide [CCP] antibodies) are frequently ordered in the evaluation of patients with suspected rheumatoid arthritis (RA) and considered to be specific biomarkers for RA. The 2010 American College of Rheumatology/European Alliance of Associations for Rheumatology (ACR/EULAR) classification criteria for RA include both ACPA and rheumatoid factor in their scoring system, despite limited standardization of commercially available anti-CCP antibody tests. In an attempt to overcome this limitation, the classification criteria recommends using multiples of the assay-specific upper limit of normal (ULN) to normalize results and standardize classification. This study evaluates the correlation between normalized results from different assays and the concordance in result classification according to the ACR/EULAR criteria. Methods A total of 265 samples with ACPA ordered as part of routine clinical care were tested on four commercial anti-CCP antibody assays, including QUANTA Lite CCP3 IgG ELISA (Werfen) (Negative: &lt;20 Units), QUANTA Flash CCP3 chemiluminescence immunoassay (Werfen) (Negative: &lt;20 Chemiluminescent Units), EUROIMMUN Anti-CCP ELISA (IgG) (EUROIMMUN) (Negative: &lt;=5 Relative Units/mL), and Elecsys anti-CCP electrochemiluminescence immunoassay (Roche) (Negative: &lt;17.0 Units/mL). The QUANTA Lite and EUROIMMUN ELISA were performed on the Agility platform (Dynex), QUANTA Flash was performed on BioFlash platform (Werfen), and Elecsys anti-CCP was performed on Cobas e601 platform (Roche). All testing was performed according to manufacturer’s instructions. Results from each assay were converted to the multiples of assay-specific ULN as the normalized results. Regression analysis was performed, and the coefficient of determination (R²) was calculated to assess the correlation between paired assays. The concordance in result classification across assays was also investigated using both assay specific cut-offs and the ACR/EULAR criteria-defined cut-offs: Negative (&lt;=1xULN), Low positive (&gt;1xULN and &lt;3xULN), High positive (&gt;=3xULN). Results Using assay-specific cut-offs, 63 samples were negative on all assays. 202 samples were positive on at least one assay, of which 79 (39%) were positive across all assays. The overall concordance of qualitative result was 54% ([63+79]/265). After result normalization using multiples of assay-specific ULNs, the highest correlation was observed between the EUROIMMUN ELISA and Elecsys anti-CCP (R²=0.83), despite differences in methodology and manufacturer. The lowest correlation was observed between QUANTA Lite and QUANTA Flash (R²=0.49), even though both are from the same manufacturer although methodologies differ. When applying the criteria-defined cut-offs, 64 samples were negative on all assays. 130 samples were classified as low positive on at least one assay; however, only 3 (2%) samples were classified as low positive across all assays. 103 samples were classified as high positive on at least one assay, of which 54 (52%) were classified as high positive across all assays. With result normalization, the overall concordance in result classification across all assays using the criteria-defined cut-offs were 46% ([64+3+54]/265). Conclusion Despite normalization using multiplies of assay-specific ULN values, the inter-assay correlation remains suboptimal, and the concordance in result classification is limited. These findings suggest that the anti-CCP antibody results from different assays may not be interchangeable even after normalization as recommended by current criteria, potentially impacting disease classification.