Citations

Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood ( n = 6454) and lung ( n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank–derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Abstract Purpose: Pancreatic ductal adenocarcinoma (PDAC) frequently recurs after neoadjuvant therapy (NT) and curative-intent resection. Although major pathologic response predicts favorable outcomes, most patients achieve only minor response with a heterogeneous recurrence risk. We asked whether the spatial organization of residual PDAC encodes clinically relevant biology beyond residual tumor burden. Experimental Design: In a retrospective cohort of 203 patients with resected PDAC treated with NT and restricted to minor pathologic response, routine hematoxylin and eosin (H&E) whole-slide images were segmented into cancer and stroma using an artificial intelligence–enabled pipeline. Spatial composition (patch density, edge density) and configuration (compactness/complexity, intermixing) were quantified and tested for associations with disease-free survival (DFS) using multivariable models adjusted for standard clinicopathologic factors. Results: Shorter DFS was associated with a fragmented, interface-rich tumor–stroma ecology featuring higher edge density and diversity and reduced homotypic aggregation, independent of clinicopathologic variables. Two spatial risk models were independently prognostic: (i) cancer mean shape index plus stromal shape index variability [adjusted hazard ratio (HR), 1.71; P = 0.003] and (ii) mean stromal patch area plus edge density (adjusted HR, 2.19; P = 0.002). Both models stratified outcomes in which pathologic response grading and residual cancer area did not. High-risk configurations were further associated with reduced intratumoral tumor-infiltrating lymphocyte (TIL) density and infiltration ratio, with relative TIL accumulation at the cancer periphery and within the stroma, consistent with an immune-excluded phenotype. Conclusions: Residual cancer–stroma topology quantified from standard H&E slides yields independent prognostic signals after NT in PDAC, provides a cellular immune correlate for spatial risk, and motivates prospective validation and spatially informed adjuvant strategies.

Importance Although the Martin-Hopkins equation is widely validated and used to estimate low-density lipoprotein cholesterol (LDL-C) for clinical care, a simplified equation could streamline implementation and enable broader adoption. Objective To develop a simplified machine learning–based alternative to the Martin-Hopkins equation using multivariate adaptive regression splines (LDL-C–MH-MARS) and compare its performance with the Friedewald (LDL-C–F), Sampson–National Institutes of Health (LDL-C–S), Modified Sampson (LDL-C–MS), and Martin-Hopkins (LDL-C–MH) equations. Design, Setting, and Participants The Very Large Database of Lipids is a cross-sectional database of clinical lipid measurements from a population-representative convenience sample of adult and pediatric patients. Lipid measurements were performed by Vertical Auto Profile ultracentrifugation between October 1, 2015, and June 30, 2019. The study included patients with complete lipid panel data who were randomly assigned to a training set and a test set. External validation against preparative ultracentrifugation-based LDL-C measurements was performed in reference laboratory datasets from the Mayo Clinic (broad LDL-C concentrations) and the Further Cardiovascular Outcomes Research With Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Inhibition in Subjects with Elevated Risk (FOURIER) trial (observations from patients with low LDL-C concentrations while taking evolocumab). Study data were analyzed from January to October 2025. Exposures LDL-C–F, LDL-C–S, LDL-C–MS, LDL-C–MH, and LDL-C–MH-MARS equations. Main Outcomes and Measures Accuracy of estimated vs ultracentrifugation-measured LDL-C concentration based on bias, root mean square error (RMSE), and concordance by guideline-based categories. Results The study included 4 939 528 patients (mean [SD] age, 56 [16] years; 2 635 486 female [53%]) with complete lipid panel data who were randomly assigned to a training set (n = 3 292 889) and a test set (n = 1 646 639). LDL-C–MH-MARS equation demonstrated a very low median (IQR) bias of −0.1 (−2.1 to 1.8) mg/dL (to convert to millimoles per liter, multiply by 0.0259), comparable with LDL-C–MH. The median (IQR) difference between the MARS and original Martin-Hopkins equations (ie, LDL-C–MH-MARS – LDL-C–MH) was −0.5 (−1.2 to 0) mg/dL, further suggesting comparability between the 2 methods. The RMSE was smallest for LDL-C–MH-MARS (4.7 mg/dL) and LDL-C–MH (4.9 mg/dL), followed by LDL-C–S (5.8 mg/dL), LDL-C-MS (6.0 mg/dL), and LDL-C–F (7.2 mg/dL). The proportion of patients correctly classified according to clinical categories was nearly identical for LDL-C–MH-MARS (89.7%) and LDL-C–MH (89.6%) but lower for LDL-C–S (86.3%), LDL-C–MS (84.7%), and LDL-C–F (83.1%). The LDL-C–MH-MARS, LDL-C–MH, LDL-C–MS, LDL-C–S, and LDL-C–F equations underestimated LDL-C concentration in 16%, 17%, 28%, 39%, and 60%, respectively, when classifying LDL-C less than 70 mg/dL in patients with triglyceride concentrations of 200 to 399 mg/dL (to convert to millimoles per liter, multiply by 0.0113). The patterns of results were similar in external validation datasets, with the LDL-C–MH-MARS and LDL-C–MH equations demonstrating the highest accuracy. Conclusions and Relevance Study results suggest that the new machine learning–based LDL-C equation provided results comparable with those of the original Martin-Hopkins method while simplifying implementation to a single equation.

Abstract Context Biochemical test results are central to clinical decision-making for the diagnosis and management of Cushing syndrome (CS). With emerging research and increasing availability of different tests, updated consensus on the utility of these biomarkers is warranted. Objective To establish an updated consensus on the role of biomarkers in the diagnosis and monitoring of adrenocorticotropic hormone-dependent CS, address novel therapeutic approaches, and identify areas for future research. Design A modified 2-round Delphi panel was conducted. Consensus was defined as ≥70% agreement/disagreement for Likert-scale statements or ≥70% selection of the same option for single-choice questions. Setting Participants represented a range of international expertise. Participants Forty-one participants took part in the Delphi panel, with no attrition between rounds (one nonclinician was not required to complete the second round). An 8-member Steering Committee guided statement development. Results Of statements designed to reach consensus, 45% (14/31) and 44% (11/25) statements reached consensus in Rounds 1 and 2, respectively. Notably, most panelists reported the use of late-night salivary cortisol for diagnosis of mild CS and for monitoring following pituitary surgery or medical or radiation therapy. Most panelists responded that block-and-replace therapies can be considered in patients with cyclical or severe CS, and consensus was reached that restoration of circadian rhythm is a treatment goal for patients with CS. Conclusion Areas of alignment among experts on the diagnosis and monitoring of CS are presented. The findings from this study are intended to support clinicians in their clinical decision-making and highlight priority areas for future research.

OBJECTIVE Endovascular thrombectomy (EVT) for acute large-vessel occlusion stroke is well established, yet its role in patients presenting with minor stroke symptoms (National Institutes of Health Stroke Scale [NIHSS] score < 6) remains unclear. Prior studies have not accounted for intraprocedural factors that may influence outcomes in this subgroup. METHODS The authors analyzed 5693 patients from the STAR (Stroke and Thrombectomy and Aneurysm Registry), including 398 with low NIHSS scores, to evaluate the association between procedure time (PT) and outcomes. Among patients with low NIHSS scores, propensity score matching was used to compare outcomes between those with PT ≤ 35 versus > 35 minutes, a cutoff defined using receiver operating characteristic curve analysis. The authors performed a meta-analysis of studies reporting best medical management (BMM) outcomes in patients with low NIHSS scores. To compare these with EVT-treated patients, a matched BMM comparator cohort using stratification on pooled baseline characteristics was constructed. Outcomes included 90-day functional independence (modified Rankin Scale [mRS] scores 0–2), intracranial hemorrhage, and mortality. RESULTS PT had a stronger negative effect on outcomes in patients with low NIHSS scores compared with those with high scores, with a steeper decline in functional independence per minute of PT (slope: –0.45% vs –0.21%; p = 0.03 for interaction). Among patients with low scores, PT ≤ 35 minutes was associated with higher 90-day functional independence compared with the propensity score–matching cohort with PT > 35 minutes (82.6% vs 59.0%, p < 0.001). When benchmarked against BMM (75.2% mRS scores 0–2), patients undergoing EVT within 35 minutes had superior outcomes (85.1%, p = 0.047). In contrast, EVT with PT > 35 minutes resulted in worse outcomes than BMM (mRS scores 0–2: 59.8%, p = 0.008). The number needed to treat for PT ≤ 35 minutes was 10, whereas PT > 35 minutes yielded a number needed to harm of 6. CONCLUSIONS PT critically modulates the benefit of EVT in minor stroke. While efficient EVT yields better outcomes than BMM, prolonged procedures are associated with harm. These findings may explain prior inconsistent evidence on EVT in patients with low NIHSS scores and underscore the need to individualize procedural thresholds in this population.

Abstract Cardiovascular disease is the leading cause of morbidity and mortality globally, imposing a substantial patient burden. Digital biomarkers derived from digital health technologies enable quantifiable, near-continuous, real-world capture of pathophysiological signals and are increasingly used across cardiovascular medicine. Their growth is often supported by big data analytics, artificial intelligence and connected sensors within the Internet of Things. This scientific statement systematically reviews digital biomarkers, their clinical utility across the cardiovascular care continuum, and summarizes major methodological and implementation challenges. We searched PubMed/MEDLINE, Embase and Scopus for phase III–IV cardiovascular trials published between 1 January 2019 and 1 August 2024 that collected digital biomarkers. We identified 541 records and included 32 trials (40 reports) enrolling 32 246 participants (44.71% women; mean age 66.2 ± 11.0 years). Heart failure was the most frequent target condition (16 trials, 50%), followed by cardiac implantable electronic devices trials (12 trials, 38%). Digital biomarkers included cardiac rhythm and heart rate, blood pressure, body weight, impedance-based measures, haemodynamic pressures, and physical activity and sleep patterns captured using diverse sensor technologies. Methodological quality was good (modal quality score 5; range 3–7), although most trials were unblinded. Current studies suggest potential clinical utility in selected cardiovascular conditions. Implementation remains challenging because of measurement variability, privacy and regulatory requirements, affordability and reimbursement barriers and inequities in access. Robust validation and outcome- and cost-effectiveness evidence are still needed. Registration number: CRD42024573879.

Diffusion MRI (dMRI) enables assessment of white matter microstructural abnormalities in Alzheimer's disease (AD), and multisite datasets enable more robust modeling of non-biological variation that can confound analyses. The Alzheimer's Disease Neuroimaging Initiative (ADNI) includes over 10 dMRI protocols, necessitating robust methods to model protocol-related variability when pooling data. Here, we compared three harmonization approaches: (1) mixed-effects models, (2) ComBat-GAM, and (3) eHarmonize, a reference-based lifespan method. We assessed their ability to reduce protocol-related variability in diffusion tensor imaging fractional anisotropy (FA) and mean diffusivity (MD) while preserving associations with cognitive impairment (CI), and amyloid-beta (Aβ) and tau PET burden in 1,086 ADNI3/4 participants. All approaches yielded more closely aligned FA/MD distributions across protocols. Associations with clinical indicators of CI were highly consistent across approaches, whereas PET associations were less widespread and more variable. Overall, multiple strategies effectively modeled protocol-related variability while preserving AD-related associations.

ABSTRACT Objective To provide expert recommendations for the development of a specialty bipolar clinic that promotes best clinical practices for the delivery of safe and effective care. Methods Members of the National Network of Depression Centers (NNDC) Bipolar Clinics Work Group met in a series of 1‐h monthly video calls over 18 months to discuss all aspects of their respective institution's bipolar clinics, including services provided, administrative processes, staffing models, characteristics of patients treated, patient volumes, finances, and research. The group also invited psychiatrists from outside of the NNDC who ran large bipolar clinics to contribute their thoughts and experiences on the subject. In addition, the NNDC sent a 20‐question survey to all 27 sites asking clinic directors specific questions about their bipolar clinics, if applicable. Further meetings and discussions incorporating results from the survey took place to produce a comprehensive set of recommendations. Results Twenty‐one of 27 NNDC sites (81%) responded to the survey. Twelve of 21 (57%) sites had a specific bipolar clinic, and another 4 (19%) were looking to start one. Clinics were based in university settings. The meetings, clinic survey, and discussions resulted in 10 recommendations describing services and operations for bipolar specialty clinics. Conclusions Given the complexity of bipolar disorder, specialty clinics are important to enhance care. Clinics with a wide array of services that include consultation, medication management, bipolar‐specific psychotherapies, and patient/family psychoeducation provide the most comprehensive care. Challenges to these clinics include maintaining ongoing patient access as well as ensuring long‐term financial stability.

Background: Fecal immunochemical tests (FITs), fecal occult blood tests (FOBTs), and multitarget stool DNA (mt-sDNA) tests are convenient, noninvasive colorectal cancer (CRC) screening strategies. However, delays in or failure to complete follow-up colonoscopy (FU-CY) after a positive noninvasive test are associated with higher CRC incidence, complications, and mortality. We sought to evaluate FU-CY rates, time to colonoscopy, and compliance predictors. Patients and Methods: This retrospective cohort study linked 2 data sources: Komodo Health Data with Exact Sciences Laboratories. Data were collected from January 2016 to June 2023 and analyzed in 2024. Study participants (ages 45–75 years) were individuals with positive stool-based CRC screening tests (FIT, guaiac-based FOBT, or mt-sDNA tests). FU-CY compliance was assessed at 30-day intervals up to 365 days, and logistic regression was used to identify predictors of FU-CY. Results: Among 362,646 participants, colonoscopy compliance was 77.1% for mt-sDNA and 45.1% for FIT/FOBT ( P <.001). Overall FU-CY compliance was lowest among Asian and Black populations, but was significantly higher in these subgroups for mt-sDNA versus FIT (Asian: 74.2% vs 41.1%; Black: 71.3% vs 44.6%). The strongest predictor of compliance was use of mt-sDNA (odds ratio, 3.98; P <.001). More than half of participants across all race groups who completed FU-CY after mt-sDNA did so within the first 120 days, whereas none of the FIT/FOBT racial subgroups reached 50% completion within 365 days. Conclusions: Timely completion of colonoscopy after a noninvasive test is critical, as failure to undergo colonoscopy or delays in completion are associated with increased CRC incidence and more advanced-stage disease. These findings demonstrate that mt-sDNA use may help close CRC screening disparity gaps compared with FIT testing. FU-CY adherence is higher, and time to colonoscopy is shorter following a positive mt-sDNA test versus FIT across all racial and ethnic subgroups.

PURPOSE Precision medicine has revolutionized oncology; however, tumor biomarkers are not reflective of the heterogeneous cancer population. We evaluated NRG Oncology prostate cancer (PCa) clinical trials for demographic differences among patients with optional biospecimen collection (BC) consent and biospecimen submission (BSub). METHODS Data from 19 NRG PCa clinical trials closed before 2015 were analyzed. Patients who consented to BC and completed BSub were evaluated by race, ethnicity, median income, area deprivation index (ADI; categorized as highest v lowest three quartiles), age at enrollment, site, and year of enrollment. T/chi-square tests were used for continuous/categorical variables, respectively, followed by logistic regression. RESULTS Of the 15,648 randomized patients eligible for BC, 11,796 (75%) had specimens submitted. In all, 4,598 (82.2%) of 5,597 eligible patients consented for optional BC in nine clinical trials with a separate BC consent process (consent rates by race/ethnicity: 74.1% Black, 72.8% Hispanic/Latino, 83.8% White). A smaller proportion of Black and Hispanic/Latino patients consented to optional BC compared with those who did not (12.1% v 19.5% Black, P < .0001; 3.5% v 5.8% Hispanic, P = .0006). In univariable logistic regression models, high ADI (more socioeconomic disadvantage) was associated with a decreased likelihood for optional BC consent (odds ratio [OR], 0.67 [95% CI, 0.55 to 0.82]; P = .02), but not a decreased likelihood for BSub (OR, 0.74 [95% CI, 0.53 to 1.04]; P = .08). Multivariable models demonstrated that Black/Hispanic/Latino patients were less likely to consent to optional BC, and Black patients were less likely to have BSub ( P < .05 for all). CONCLUSION White/non-Hispanic patients and those with less socioeconomic disadvantage were more likely to consent to optional BC, whereas Black patients were less likely to have BSub. Targeted solutions are needed to improve biorepository representation so that precision medicine approaches better reflect the cancer population.