Citations

Abstract Categorical variants, or sets of genomic alterations constrained by shared properties, are pervasive across clinical, regulatory, and research domains in the biomedical ecosystem, yet their inconsistent and non-computable representation hinders data interoperability and clinical interpretation. We surveyed genomic knowledgebases spanning regulatory approvals and the biomedical literature and found that categorical variants underpin a substantial proportion of clinical genomics knowledge, but are largely described using incompatible bespoke models. To address this, we developed the GA4GH Categorical Variation Representation Specification (Cat-VRS), a constraint-based framework that provides a unified computable representation for both precise and intentionally broad categories across molecular and systemic variant domains. Cat-VRS enables harmonization of genomic knowledgebases, computable category-based search, and automated matching between assayed variants and categorical entities in clinical and research contexts. By providing a principled, extensible model for categorical variation, Cat-VRS enables computable reasoning over genomic variant categories and establishes a foundation for the standardized representation and exchange of genomic knowledge.

Abstract The human X chromosome accounts for ∼5% of the genome. Despite its size, the role of X-chromosomal variants in human diseases is not well understood, mainly due to its distinct inheritance pattern and the frequent omission of sex chromosomes from genome-wide association studies. This study used whole-genome sequencing data from 888 multiple system atrophy (MSA) cases and 7128 controls to perform an X-chromosome-wide common variant association study. Our analyses revealed two sex-differential risk loci: one located at Xq28, associated with increased risk for MSA in females [index variant: rs4898389, odds ratio (OR) = 1.69, 95% confidence interval (CI) = 1.40–2.03, P-value = 2.43 × 10⁻⁸], and another at Xp22.2 within the TBL1X gene, identified in males (index variant: rs6638956, OR = 1.48, 95%CI = 1.26–1.73, P-value = 9.92 × 10⁻⁷). In the Xq28 locus, colocalization analyses pointed to FAM3A and PLXNA3 as genes of interest. These findings emphasize the vital role of sex-differential genetic factors in the pathogenesis of MSA.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Hodgkin lymphoma provide expert, multidisciplinary recommendations for the diagnosis and treatment of Hodgkin lymphoma. The panel convenes annually to update recommendations based on a review of recently published clinical trials. This selection from the NCCN Guidelines for Hodgkin Lymphoma focuses on the management of newly diagnosed and relapsed/refractory classic Hodgkin lymphoma in adults aged 18 to 60 years.

Abstract Isolated/idiopathic rapid-eye-movement (REM)-Sleep Behavior Disorder (iRBD) is characterized by dream enactment behaviors associated with loss of REM atonia. iRBD is in most cases a prodromal synucleinopathy, and emerging evidence suggests associations between RBD and other neurological and psychiatric conditions. In this study, we performed pathway-based polygenic risk score (PRS) and rare variant burden analyses to examine these potential associations. Pathway-specific PRS were constructed from genome-wide association study summary statistics of five neurodegenerative and seven psychiatric traits across 10 biologically relevant pathway categories, including a total of 279 pathways, in 1,573 iRBD cases and 16,022 controls from the International RBD Study Group and UK Biobank. Rare variant burden tests were performed in 1,264 iRBD cases and 2,581 controls. We identified multiple potential pathways indicating shared polygenic risk between RBD and both neurodegenerative and psychiatric disorders. Lewy body diseases and post-traumatic stress disorder had the most shared polygenic risk pathways in neurological and psychiatric disorders, respectively. Two pathways, the serotonin transport pathway and the chaperone-mediated autophagy pathway, showed the strongest association with iRBD, and gene-based rare variants analyses revealed five genes associated with iRBD: GBA1 , PLEKHM1 , LRP2 , P2RX1 , and HAP1. Subsequent analysis of these genes in Parkinson’s disease and dementia with Lewy bodies replicated several associations. Together, these findings provide novel insights into the shared genetic architecture underlying iRBD, neurodegenerative disorders, and psychiatric traits, with implications for early identification and mechanistic understanding.

Abstract INTRODUCTION Sleep disruption, particularly loss of slow‐wave sleep (SWS), is common in Alzheimer's disease (AD), but its neurobiological underpinnings remain unclear. We investigated whether locus coeruleus (LC) integrity relates to SWS across the AD continuum and whether sex and perivascular spaces (PVSs) modify these associations. METHODS In a cohort (11 controls, 30 mild cognitive impairment, 17 AD dementia) we combined overnight polysomnography with LC‐sensitive magnetic resonance imaging of the LC, basal ganglia and centrum semiovale PVS ratings, and cerebrospinal fluid noradrenaline. Multivariable linear regression adjusted for demographics, disease stage, and medication use. RESULTS Higher LC integrity was associated with greater slow‐wave activity and slow oscillation power, with stronger effects in females. Basal ganglia PVS burden was related to lower SWS spectral power, whereas noradrenaline levels were not associated with sleep. DISCUSSION LC integrity, sex, and PVS burden show associations with SWS alterations in aging and AD, supporting restorative sleep as a potential therapeutic target.

This cohort study evaluates the reduction in risk of high-grade serous carcinoma among women undergoing opportunistic bilateral salpingectomy in Canada.

Abstract Recent updates to monocyte count thresholds recognize oligomonocytic chronic myelomonocytic leukemia (OM-CMML) as an early form of CMML. However, the clinical validity of these changes remains uncertain without incorporating biological and genomic factors. In this study, we analyzed a cohort of 911 patients (249 with OM-CMML, 359 with overt CMML, and 303 with myelodysplastic syndromes) using unsupervised clustering to evaluate the role of genomic determinants in refining CMML diagnosis. Our findings show that CMML molecular signatures (biallelic TET2 mutations or SRSF2-TET2 comutations) are linked to a distinct transcriptome, monocytic bias, classical monocytosis, and a higher risk of progression to overt CMML in OM-CMML cases. We developed a weighted genomic model and diagnostic workflow showing that combining genomic signatures with bone marrow monocyte frequencies in OM-CMML more accurately predicts progression to overt CMML. These findings support integrating genomic determinants and our clinic-ready diagnostic workflow into the CMML diagnostic framework to improve accuracy. Significance: Through comprehensive clinical and genomic profiling of a large patient cohort, alongside immunophenotypic and transcriptional cellular analyses, this study provides evidence that incorporating genomic determinants into the diagnostic criteria for OM-CMML improves diagnostic accuracy and refines the identification of early-stage CMML, thereby preventing misclassification.

Abstract The kinesin-5 motor protein KIF11 is crucial for mitotic spindle assembly, driving the separation of spindle poles through microtubule sliding. Src-family kinases phosphorylate KIF11 at multiple tyrosine residues within its motor domain, but the mechanistic consequences of these modifications remain unclear. Here, we dissect the role of phosphorylation at Y211 using phospho-mimetic (Y211E) and non-phosphorylatable mutants (Y211F) in biochemical, biophysical, and cellular assays. Optical trapping and Förster resonance energy transfer (FRET) analyses reveal that Y211 phosphorylation slows neck-linker docking, reducing motor velocity and force generation under load. In human cells, Y211E expression impairs bipolar spindle formation and decreases spindle pole separation velocity, while Y211F shortens steady-state spindle length. Fluorescence recovery after photobleaching (FRAP) analyses show that Y211E accelerates motor turnover on spindle microtubules, consistent with the mutant motor’s heightened load sensitivity. Together, these findings support a model in which Src-mediated phosphorylation at Y211 acts as a rheostat to tune KIF11 mechanochemistry and spindle assembly dynamics, linking cancer-relevant kinase signaling to mitotic force generation.

OBJECTIVE The aim of this study was to determine predictors of the minimum clinically important difference (MCID) in the Neck Disability Index (NDI) following cervical spinal deformity surgery. METHODS A retrospective review was performed of a prospective, multicenter adult cervical spinal deformity database. All patients had baseline and 1-year NDI scores. Patients met MCID with an improvement of NDI by 7 points between baseline and 1 year, as previously established. Baseline demographics, comorbidities, and both baseline and 1-year spinopelvic parameters were evaluated for statistical significance in a univariate logistic regression analysis. Significant variables, in addition to baseline NDI, were analyzed in a multivariable logistic regression model by backward selection with Akaike information criterion minimization. RESULTS A total of 122 patients were included with a median age of 62 (IQR 56, 69) years; 62% of patients were female. Of the 122 patients, 72 (59%) achieved NDI MCID at 1 year. Predictors of achieving MCID on univariate analysis included a lower Charlson Comorbidity Index (CCI) total score (OR 0.70, p = 0.03), depression as a comorbidity (OR 2.9, p = 0.02), lower C2 tilt at the 1-year follow-up (OR 0.92, p = 0.02), and a greater difference between 1-year postoperative C2–7 sagittal vertical axis (SVA) and preoperative C2–7 SVA (OR 0.98, p = 0.0495). On multivariable logistic regression analysis, predictors of achieving MCID included a lower CCI (OR 0.62, p = 0.03), depression as a comorbidity (OR 3.1, p = 0.059), a greater change in C2–7 SVA at the 1-year follow-up compared with baseline (OR 0.97, p = 0.055), and baseline NDI (OR 1.02, p = 0.24) with an area under the curve of 0.74. CONCLUSIONS The best-fit multivariable model included higher baseline NDI, a greater change in C2–7 SVA, patient-reported baseline depression, and lower CCI as important factors in predicting NDI MCID.

Background: Colorectal cancer (CRC) is the second leading cause of cancer-related mortality worldwide, accounting for approximately 10% of all cancer cases. Despite the proven effectiveness of conventional screening modalities such as colonoscopy and fecal immunochemical testing (FIT), their invasive nature, high cost, and limited patient compliance hinder widespread adoption. Recent advancements in artificial intelligence (AI) and bowel sound-based signal processing have enabled non-invasive approaches for gastrointestinal diagnostics. Among these, bowel sound analysis—historically considered subjective—has reemerged as a promising biomarker using digital auscultation and machine learning. Objective: This review explores the potential of AI-powered bowel sound analytics for early detection, screening, and characterization of colorectal cancer. It aims to assess current methodologies, summarize reported performance metrics, and highlight translational opportunities and challenges in clinical implementation. Methods: A narrative review was conducted across PubMed, Scopus, Embase, and Cochrane databases using the terms colorectal cancer, bowel sounds, phonoenterography, artificial intelligence, and non-invasive diagnosis. Eligible studies involving human bowel sound-based recordings, AI-based sound analysis, or machine learning applications in gastrointestinal pathology were reviewed for study design, signal acquisition methods, AI model architecture, and diagnostic accuracy. Results: Across studies using convolutional neural networks (CNNs), gradient boosting, and transformer-based models, reported diagnostic accuracies ranged from 88% to 96%. Area under the curve (AUC) values were ≥0.83, with F1 scores between 0.71 and 0.85 for bowel sound classification. In CRC-specific frameworks such as BowelRCNN, AI models successfully differentiate abnormal bowel sound intervals and spectral patterns associated with tumor-related motility disturbances and partial obstruction. Distinct bowel sound-based signatures—such as prolonged sound-to-sound intervals and high-pitched “tinkling” proximal to lesions—demonstrate the physiological basis for CRC detection through bowel sound-based biomarkers. Conclusions: AI-driven bowel sound analysis represents an emerging, exploratory research direction rather than a validated colorectal cancer screening modality. While early studies demonstrate physiological plausibility and technical feasibility, no large-scale, CRC-specific validation studies currently establish sensitivity, specificity, PPV, or NPV for cancer detection. Accordingly, bowel sound analytics should be viewed as hypothesis-generating and potentially complementary to established screening tools, rather than a near-term alternative to validated modalities such as FIT, multitarget stool DNA testing, or colonoscopy.