Citations

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

Abstract Methods that map genetic risk to cells do not directly test whether spatially organized ligand–receptor (LR) gene annotations carry conditional heritability association. Here we introduce EdgeMap, which scores each gene by the spatial activity of its LR contexts in spatial transcriptomics data, maps these scores alongside cell-intrinsic annotations to SNP-level LD scores, and tests both jointly against GWAS summary statistics. Across 17 traits and five human tissues, edge z -scores are systematically higher in biologically matched tissues: all 15 traits with both matched and unmatched tissue classes show this ordering (median Δ z = 1.51 ; sign P = 3.1 × 10 −5 ), and 11 of 13 nominal-positive associations concentrate in the biologically matched set ( P = 1 × 10 −4 ). The pattern survives broad LR-gene-class and cell-type composition controls. Donor-level cross-section summaries, independent GWAS replication for LDL and CAD, and cell-segmented Visium HD liver data provide convergent support. A secondary analysis prioritizes constituent genes within active LR contexts; sixteen of 31 prioritized genes are absent from standard gene-level methods. These results establish spatially weighted LR-gene annotations as a complementary layer for interpreting complex-trait genetic architecture.

ABSTRACT Cataract is a leading cause of visual impairment worldwide, and its prevalence is increasing with population aging. The majority are age‐related cataracts (ARC), clinically classified into nuclear, cortical, and posterior subcapsular cataracts (PSC) by opacity location. Mechanisms of cataractogenesis remain incompletely understood. While cortical and nuclear cataracts are largely attributed to crystallin aggregation, such protein‐centric mechanisms fail to explain the early onset and axial location of PSC. Morphologically, PSC resembles posterior capsule opacification (PCO), a secondary cataract driven by epithelial–mesenchymal transition (EMT) of lens epithelial cells (LECs), suggesting LEC‐EMT may also contribute to PSC. Using clinically stratified human lens samples, we confirmed EMT marker expression across PSC subtypes. Transcriptomic profiling revealed that LECs, the lens's sole metabolically active cells, in age‐related PSC (ARC‐PSC), compared with age‐related nuclear cataract (ANC) and clear lenses, exhibit elevated EMT signatures tightly linked to senescence‐associated inflammatory signaling. Aqueous humor (AqH) profiling demonstrated a pro‐inflammatory milieu across PSC subtypes, with IL‐17A uniquely elevated in ARC‐PSC, consistent with transcriptomic findings. Integrated analyses support a model in which senescence functions as an upstream driver, whereby senescent LECs release SASP factors, including IL‐17A, that activate NF‐κB signaling to amplify inflammation, reinforce senescence, and drive EMT. In vitro, senolysis and IL‐17A blockade disrupted this loop, attenuating senescence‐ and EMT‐associated phenotypes. Collectively, our study demonstrates that senescent LECs sustain an IL‐17A–NF‐κB circuit that drives EMT and accelerates ARC‐PSC progression, positioning ARC‐PSC as a unique human context to study senescence‐induced epithelial remodeling in aging tissues.

Abstract Spatial transcriptomics links gene expression to tissue architecture, but detecting spatially variable genes at atlas scale remains difficult because biologically relevant patterns are multiscale, sparse, and often non-parametric. Here we show that FlashS, a frequency-domain kernel test using random Fourier features, sparse sketching, and a kurtosis-corrected null, retains Gaussian-kernel flexibility at near-linear per-gene cost without permutation. Across 50 benchmark datasets spanning 9 spatial transcriptomics platforms, F lash S achieves the highest ranking accuracy among 14 compared methods while maintaining calibrated inference under simulation and full-atlas permutation. In human heart tissue, it recovers a mitochondrial biogenesis program that co-localizes with ventricular cardiomyocytes. On the Allen Brain MERFISH atlas containing 3.94 million cells, F lash S completes in minutes on a single workstation and separates biological signal from negative-control barcodes even when p-values saturate.

Background: Healing of the tendon-bone interface (TBI) after rotator cuff injury is limited, often leading to scar-mediated repair. Decellularized tendon fibrocartilage–bone composite (dTFBC) and bone marrow mesenchymal stem cell sheets (BMSCS) improve repair in preclinical models, but full scaffold encapsulation with mechanical preconditioning remains unexplored. Purpose: To evaluate TBI regeneration using mechanically preconditioned, BMSCS-encapsulated dTFBC scaffolds in a rabbit model. Study Design: Controlled laboratory study. Methods: A total of 48 male New Zealand White rabbits were randomized into 4 groups (n = 12 each): (1) standard repair (control); (2) repair with dTFBC; (3) repair with dTFBC-BMSCS; and (4) repair with mechanically preconditioned dTFBC-BMSCS (mdTFBC-BMSCS). Healing at 12 weeks was assessed via gross observation, histomorphological and immunohistochemical analyses, and biomechanical testing. Results: The mdTFBC-BMSCS group demonstrated a higher ultimate failure load (mean, 203.9 ± 65.6 N) than both the control (118 ± 37.4 N; P = .003) and dTFBC groups (127 ± 44.1 N; P = .008), with no significant difference between the 2 BMSCS-treated groups. Histological analysis revealed enhanced fibrocartilage formation, improved collagen fiber organization, and reduced inflammation infiltration at the TBI in the mdTFBC-BMSCS group. Immunohistochemical analysis showed greater collagen type 2 alpha 1 chain-, interleukin 10-, and arginase 1-positive areas in the mdTFBC-BMSCS group than in the control and dTFBC groups. Conclusion: Mechanically preconditioned, fully BMSCS-encapsulated dTFBC scaffolds promoted TBI regeneration, with enhanced cellular integration, fibrocartilage formation, and favorable biomechanical performance. Clinical Relevance: This biomimetic scaffold strategy may enhance biological healing and reduce the risk of retear after rotator cuff repair.

Abstract Coarsening Visium HD resolution from 8 to 64 µ m can flip cell-type co-localization from negative to positive ( r = −0.12 → +0.80 ), yet many widely used compositional deconvolution workflows require coarsening or subsampling at million-bin scale. Here we introduce FlashDeconv, which combines leverage-score importance sampling with sparse spatial regularization to achieve competitive benchmark accuracy while processing 1.6 million bins in 153 seconds on commodity hardware. Systematic multi-resolution analysis of Visium HD mouse intestine reveals a tissue-specific resolution horizon (8–16 µ m)—the scale at which this sign inversion occurs—validated by Xenium ground truth. Below this horizon, FlashDeconv provides, to our knowledge, the first sequencing-based quantification of Tuft cell chemosensory niches (15.3-fold stem cell enrichment). In a 1.6-million-bin human colorectal cancer cohort, FlashDeconv uncovers neutrophil inflammatory microdomains co-localized with immunoregulatory dendritic cells (mRegDC) at the tumor–stroma interface—spatial niches largely missed by discrete-label summaries, with RCTD doublet mode labeling only 2.3% of hotspot bins as neutrophil singlets.

Abstract Background Lung adenocarcinoma in never-smokers is a major public health burden, especially among East Asian women. Polygenic risk scores (PRSs) are promising for risk stratification but are primarily developed in European-ancestry populations. We aimed to develop and validate single- and multi-ancestry PRSs for East Asian never-smokers to improve lung adenocarcinoma risk prediction. Methods PRSs were developed using genome-wide association study summary statistics from East Asian (8002 cases; 20 782 controls) and European (2058 cases; 5575 controls) populations. Single-ancestry models included a PRS with 25 single nucleotide variants (PRS-25), PRS clumping and thresholding (CT), and LDpred2; multi-ancestry models included LDpred2 plus European PRS-128, PRS-CSx, and clumping and thresholding, super learning, empirical Bayes (CT-SLEB). Performance was evaluated in independent East Asian data from the Female Lung Cancer Consortium and externally validated in the Nanjing Lung Cancer Cohort. We assessed predictive accuracy via area under the curve operating procedure (AUC), with 10-year and (ages 30-80 years) absolute risks estimates. Results The best multi-ancestry PRS, using East Asian and European data via CT-SLEB, outperformed the best East Asian-only (LDpred2; AUC = 0.629, 95% confidence interval [CI] = 0.618 to 0.641), achieving an AUC of 0.640 (95% CI = 0.629 to 0.653) and odds ratio of 1.71 (95% CI = 1.61 to 1.82) per standard deviation increase. Nanjing Lung Cancer Cohort validation confirmed robust performance (AUC = 0.649, 95% CI = 0.623 to 0.676). The top 20% PRS group had a 3.92-fold higher lung adenocarcinoma risk than the bottom 20%. Further, the top 5% PRS group reached a 6.69% lifetime absolute risk. Notably, this group reached the average population 10-year lung adenocarcinoma risk at age 50 years (0.42%) by age 41 years, 9 years earlier. Conclusions Multi-ancestry PRS approaches enhance lung adenocarcinoma risk stratification in East Asian never-smokers, with consistent external validation, suggesting future clinical utility.

Opioid use disorders (OUDs) pose a substantial global health burden, with methadone maintenance treatment (MMT) widely adopted as an intervention; however, MMT is associated with immunosuppression, metabolic disturbances, and dysbiosis of the gut microbiota. Despite the potential of acupuncture in reducing methadone dosages and opioid addiction, the underlying biological mechanisms remain unclear. Therefore, we aimed to integrate clinical trial data with multi-omics analysis, including single-cell sequencing, transcriptomics, metabolomics, and metagenomics, to evaluate the effects of acupuncture in patients undergoing MMT. We collected peripheral blood mononuclear cells, plasma, and fecal samples from 48 MMT participants in a randomized, placebo-controlled trial. Participants were divided into acupuncture ( n = 25) and sham-acupuncture ( n = 23) groups. After 8 weeks of intervention, 84% of patients in the acupuncture group achieved ≥20% reduction in methadone dosage, compared to 39% in the sham-acupuncture group ( P < 0.01). Our findings revealed that acupuncture may activate the defense response to viruses, with altered immune cell functions in classical monocytes correlating with clinical responses to reduced methadone doses. Acupuncture might ameliorate intestinal microbial disruptions caused by OUD by up-regulating Bilophila and modulating bile acid metabolism. Furthermore, acupuncture up-regulated galectin-9 (LGALS9)-mediated intercellular communication between classical monocytes and other immune subsets. To further validate the mechanistic link between bile acid metabolism and immune regulation, we conducted in vitro experiments using THP-1 monocytes treated with cholic acid. The results showed that bile acid exposure suppressed galectin-9 and IFN-γ expression, while low-dose bile acid (simulating acupuncture effects) partially reversed this effect. These findings support a bile acid–galectin–interferon axis that may be modulated by acupuncture in OUD. Collectively, our results provide clinical and mechanistic evidence supporting acupuncture as a potential adjunct therapy to mitigate the adverse effects of long-term opioid use.

Abstract Different large language models (LLMs) have the potential to complement one another. We introduce an iterative multi-LLM consensus framework for annotating single-cell RNA sequencing data. This framework outperforms the best state-of-the-art method by nearly 15% in mean accuracy (77.3% vs 61.3%) across 50 diverse datasets from 26 tissues, encompassing over 8 million cells. By leveraging cross-model deliberation, our framework quantifies uncertainty, identifies ambiguous clusters for expert review, provides transparent reasoning chains, and minimizes the effort and expertise needed for cell type annotation in large-scale studies. Additionally, our framework enables users to seamlessly integrate new LLMs.

Abstract We conducted this systematic review and meta-analysis to clarify the trend of precocious puberty (PP) incidence after the COVID-19 outbreak and explore potential contributing factors, such as age at presentation and body mass index (BMI) SD score (SDS). Children visiting pediatric endocrinology clinics for the first time for suspected PP were included. We searched databases until February 28, 2023, for studies reporting various indicators of PP incidence before and during the pandemic. Total numbers of events and observations were recorded. A meta-analysis was performed to compare the odds of PP, BMI SDS, and age at presentation between the 2 periods. The dose-response relationships between time points (by number of years away from the pandemic) and PP risk were explored. In summary, a total of 32 studies including 24 200 participants were recruited. The COVID-19 pandemic was associated with the increasing odds of PP among children referred for a suspicious condition (odds ratio = 1.96; 95% CI, 1.56-2.47; I2 = 54%; P &lt; .001). Sensitivity analysis confirmed the robustness of the findings. The BMI SDS did not vary between the 2 periods, whereas age at presentation was lower after the pandemic. Precocious puberty incidence increased more rapidly during the pandemic period than during the prepandemic period. Trial registration: International Prospective Register of Systematic Reviews (PROSPERO; identifier: CRD42023402212)