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 Background Breast cancer genome-wide association studies (GWAS) have identified more than 200 susceptibility loci, but most studies are dominated by European and East Asian populations. Methods We analyzed breast cancer GWAS summary statistics from African (AFR), East Asian (EAS), European (EUR), and Hispanic/Latina (H/L) samples (159,297 cases and 212,102 controls). We estimated logit-scale SNP-based heritability, polygenicity, and cross-ancestry genetic correlation, partitioned heritability across functional annotations, and integrated GWAS results with the Tabula Sapiens single-cell atlas using scDRS+. Results The logit-scale heritability of breast cancer ranged from ℎ 2 =0.47 (SE = 0.07) in EAS to AFR ℎ 2 =0.61 (SE = 0.10), with no significant differences across ancestries (p=0.63). The estimated number of susceptibility markers in a sparse normal-mixture effects model also varied from 4,446 (SE = 3,100) in EAS to 8,308 (SE = 2,751) in AFR, but differences were not significant across ancestries (p=0.55). Cross-sample genetic correlations varied, with the strongest correlation between EUR and EAS (𝜌 = 0.79, SE = 0.08) and weakest between AFR and H/L (𝜌 = 0.26, SE = 0.24). Regulatory annotations were enriched for breast cancer heritability across samples. Integration with single-cell expression profiles implicated ancestry-shared associations with innate immune, secretory epithelial, and stromal cell types. Conclusion These results indicate substantial cross-ancestry sharing of breast cancer polygenic architecture, highlight a consistent contribution of regulatory variation, and identify convergent cellular contexts that motivate functional follow-up and inform expectations for the transferability and attainable performance of common-variant risk prediction across populations.

Abstract Introduction: Breast cancer genome-wide association studies (GWAS) have identified over 200 susceptibility loci, many replicated in diverse populations. However, cross-ancestry evaluation of breast cancer genetic architecture remains limited. We examined breast cancer genetic architecture using GWAS summary results from European (EUR; cases (ca) = 188,474, controls (co) = 96,201), East Asian (EAS; ca = 20,393, co = 86,329), African American (AA; ca = 9,235, co = 10,184), and US Hispanic/Latina and Latin American (H/L; ca = 2,396, co =7,468) studies. Methods: GWAS results were derived from the Breast Cancer Association Consortium, the African Ancestry Breast Cancer Genetics Consortium (AABCG), Biobank Japan, and a meta-analysis of five studies of H/L women with breast cancer. Linkage disequilibrium (LD) scores were generated for EUR, EAS, and AMR using the 1000 Genomes Project, while AA LD scores were derived from a subset of AABCG controls. Heritability was estimated for each ancestry group using LD score regression. Genetic correlations between populations were assessed via Popcorn. Polygenicity was analyzed using GENESIS; however, due to the limited sample size in the H/L studies, these estimates were restricted to AA, EAS, and EUR. Enrichment of heritability across regulatory elements was evaluated using stratified LD score regression across all populations. Results: The logit-scale heritability and corresponding standard error (SE) were 0.466 (0.066) for EAS, 0.501 (0.050) for EUR, 0.588 (0.360) for H/L, and 0.614 (0.095) for AA. The estimated number of independent susceptibility loci was 4,446 for EAS, 5,235 for EUR, and 8,308 for AA. Using a clumping and thresholding approach, an optimal set of common variants were projected to explain 38.6% (EUR), 39.4% (EAS), and 26.2% (AA) of genetic variance for samples of 100,000 cases and 100,000 controls with AUCs from corresponding estimated polygenic risk scores (PRSs) of 0.621 (EUR), 0.634 (EAS), and 0.611 (AA). Genetic correlations were strongest between EUR and EAS (ρ = 0.79, SE = 0.08) and EUR and H/L (ρ = 0.68, SE = 0.21), and weakest between AA and EAS (ρ = 0.42, SE = 0.14) and AA and H/L (ρ = 0.26, SE = 0.24). Among 73 genomic features, we found significant (P < 0.05/73) enrichment in heritability in EUR for ‘ancient promoter’ regions, transcription factor binding sites, H3K4me3, ‘super-enhancers’, H3K4me1, H3K27ac; in EAS for ‘super-enhancers’; and in AA for H3K27ac. No genomic features were significantly enriched in H/L, likely due to limited power. Conclusion: These findings suggest a shared breast cancer genetic architecture across diverse populations, as well as the potential for a similar level of breast cancer risk stratification by PRS in these populations. Expanding GWAS in underrepresented populations is essential to improve genetic risk predictions and foster equitable cancer prevention. Citation Format: James L. Li, Maria Zanti, Jacob Williams, Om Jahagirdar, Guochong Jia, Qiang Hu, Jean-Tristan Brandenburg, Li Yan, Weang-Kee Ho, Jingmei Li, José P. Miranda, Devika Godbole, Julie-Alexia Dias, Leila Dorling, Wenlong C. Chen, Nicholas Boddicker, Ying Wang, Alicia Martin, Martin J. Zhang, Yan Zhang, Joe Dennis, Esther M. John, Gabriela Torres-Mejia, Larry Kushi, Jeffrey Weitzel, Susan L. Neuhausen, Luis Carvajal-Carmona, Christopher Haiman, Elad Ziv, Laura Fejerman, Wei Zheng, Dezheng Huo, Douglas Easton, Nilanjan Chatterjee, Peter Kraft, Montserrat Garcia-Closas, Wendy Wong, Kyriaki Michailidou, Qianqian Zhu, Diptavo Dutta, Thomas U. Ahearn, Haoyu Zhang. Genetic architecture of breast cancer across diverse populations: Assessing heritability, genetic correlation, and polygenicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 2282.

AbstractIschemia‒reperfusion (I/R) is a common complication in the clinical treatment of acute myocardial infarction (MI), in which cardiomyocytes play a pivotal role in the recovery of cardiac function after reperfusion injury. The expression of numerous circular ribonucleic acids (circRNAs) is disrupted in I/R‐induced cardiac damage, but the potential role of circRNAs in I/R damage has not been fully elucidated. The purpose of the present study was to clarify the biological action and molecular mechanism of circRNA 002166 (also termed circCL2L13) in postmyocardial I/R. Oxygen–glucose deprivation/reoxygenation (OGD/R) in an in vivo model was performed to simulate I/R damage. real‐time polymerase chain reaction analysis was also conducted to evaluate the relationships of the SOD1, SOD2, NRF2, HO1 and GPX4 indicators with oxidative stress injury. TUNEL immunofluorescence was used to evaluate the degree of cardiomyocyte apoptosis in the different treatment groups. The circBCL2L13 level was markedly upregulated in myocardial tissues from a mouse I/R model. Overexpression of circBCL2L13 markedly attenuated the expression of oxidative stress‐related genes and apoptosis in OGD/R‐induced cardiomyocytes. A mechanistic study revealed that circBCL2L13 functions as a ceRNA for miR‐1246 and modulates paternally expressed gene 3 (PEG3). Eventually, circBCL2L13 was proven to regulate PEG3 by targeting miR‐1246, thereby protecting against OGD/R‐induced cardiomyocyte oxidative damage and apoptosis. In conclusion, our study confirmed that the circBCL2L13/miR‐1246/PEG3 axis suppressed the progression of OGD/R injury in cardiomyocytes, which might lead to new therapeutic strategies for cardiac I/R injury.

Background Nephritis is a common manifestation of IgA vasculitis and is morphologically indistinguishable from IgA nephropathy. While MEST-C scores are predictive of kidney outcomes in IgA nephropathy, their value in IgA vasculitis nephritis has not been investigated in large multiethnic cohorts. Methods Biopsies from 262 children and 99 adults with IgA vasculitis nephritis ( N =361) from 23 centers in North America, Europe, and Asia were independently scored by three pathologists. MEST-C scores were assessed for correlation with eGFR/proteinuria at biopsy. Because most patients ( N =309, 86%) received immunosuppression, risk factors for outcomes were evaluated in this group using latent class mixed models to identify classes of eGFR trajectories over a median follow-up of 2.7 years (interquartile range, 1.2–5.1). Clinical and histologic parameters associated with each class were determined using logistic regression. Results M, E, T, and C scores were correlated with either eGFR or proteinuria at biopsy. Two classes were identified by latent class mixed model, one with initial improvement in eGFR followed by a late decline (class 1, N =91) and another with stable eGFR (class 2, N =218). Class 1 was associated with a higher risk of an established kidney outcome (time to ≥30% decline in eGFR or kidney failure; hazard ratio, 5.84; 95% confidence interval, 2.37 to 14.4). Among MEST-C scores, only E1 was associated with class 1 by multivariable analysis. Other factors associated with class 1 were age 18 years and younger, male sex, lower eGFR at biopsy, and extrarenal noncutaneous disease. Fibrous crescents without active changes were associated with class 2. Conclusions Kidney outcome in patients with biopsied IgA vasculitis nephritis treated with immunosuppression was determined by clinical risk factors and endocapillary hypercellularity (E1) and fibrous crescents, which are features that are not part of the International Study of Diseases of Children classification.

ImportanceLittle is known about regional nodal irradiation (RNI) practice patterns or rates of locoregional recurrence (LRR) with and without RNI in patients with limited nodal disease and favorable biology treated with modern surgical and systemic therapy, including approaches that de-escalate those latter treatments.ObjectiveTo investigate how often patients with low–recurrence score breast cancer with 1 to 3 nodes involved receive RNI, incidence and predictors of LRR, and associations between locoregional therapy and disease-free survival.Design, Setting, and ParticipantsIn this secondary analysis of the SWOG S1007 trial, patients with hormone receptor-positive, ERBB2-negative breast cancer, and a Oncotype DX 21-gene Breast Recurrence Score assay result of no more than 25, were randomized to endocrine therapy alone vs chemotherapy then endocrine therapy. Prospectively collected radiotherapy information was collected from 4871 patients treated in diverse settings. Data were analyzed June 2022 to April 2023.ExposureReceipt of RNI (targeting at least the supraclavicular region).Main Outcome(s) and Measure(s)Cumulative incidence of LRR was calculated by locoregional treatment received. Analyses were assessed for associations between invasive disease-free survival (IDFS) and locoregional therapy, adjusted for menopausal status, treatment group, recurrence score, tumor size, nodes involved, and axillary surgery. Radiotherapy information was recorded in the first year after randomization, so survival analyses were landmarked as starting at 1 year among those still at risk.ResultsOf 4871 female patients (median [range] age, 57 [18-87] years) with radiotherapy forms, 3947 (81.0%) reported radiotherapy receipt. Of 3852 patients who received radiotherapy and had complete information on targets, 2274 (59.0%) received RNI. With a median follow-up of 6.1 years, the cumulative incidence of LRR by 5 years was 0.85% among patients who received breast-conserving surgery and radiotherapy with RNI; 0.55% after breast-conserving surgery with radiotherapy without RNI; 0.11% after mastectomy with postmastectomy radiotherapy; and 1.7% after mastectomy without radiotherapy. Similarly low LRR was observed within the group assigned to endocrine therapy without chemotherapy. The rate of IDFS did not differ by RNI receipt (premenopausal: hazard ratio [HR], 1.03; 95% CI, 0.74-1.43; P = .87; postmenopausal: HR, 0.85; 95% CI, 0.68-1.07; P = .16).Conclusions and RelevanceIn this secondary analysis of a clinical trial, RNI use was divided in the setting of biologically favorable N1 disease, and rates of LRR were low even in patients who did not receive RNI. Disease-free survival was not associated with RNI receipt; omission of chemotherapy among patients similar to those enrolled in the S1007 trial is not an independent indication for use of RNI.

AbstractPurposeAs a typical chronic kidney disease (CKD), hypertensive nephrosclerosis (HN) is a common syndrome of hypertension, characterized by chronic kidney microvascular damage. Early diagnosis of microvascular damage using conventional ultrasound imaging encounters challenges in sensitivity and specificity owing to the inherent diffraction limit. Ultrasound localization microscopy (ULM) has been developed to obtain microvasculature and microvascular hemodynamics within the kidney, and would be a promising tool for the early diagnosis of CKD.MethodsIn this study, the advantage of quantitative indexes obtained by using ULM (mean arterial blood flow speeds of different segments of interlobular arteries) over indexes obtained using conventional clinical serum (β2‐microglobulin, serum urea nitrogen, and creatinine) and urine (24‐h urine volume and urine protein) tests and ultrasound Doppler imaging (peak systolic velocity [PSV], end‐diastolic velocity [EDV], and resistance index [RI]) and contrast‐enhanced ultrasound imaging (CEUS; rise time [RT], peak intensity [IMAX], mean transit time [mTT], and area under the time‐intensity curve [AUC]) for early diagnosis of HN were investigated. Examinations were carried out on six spontaneously hypertensive rats (SHR) and five normal Wistar–Kyoto (WKY) rats at the age of 10 weeks.ResultsThe experimental results show that the indicators derived from conventional clinical inspections (serum and urine tests) and ultrasound imaging (PSV, EDV, RI, RT, IMAX, mTT, and AUC) do not show significant difference between hypertensive and healthy rats (p > 0.05), while the TTP of the SHR group (28.52 ± 5.52 s) derived from CEUS is significantly higher than that of the WKY group (18.68 ± 7.32 s; p < 0.05). The mean blood flow speed in interlobular artery of SHR (12.47 ± 1.06 mm/s) derived from ULM is significantly higher than that of WKY rats (10.13 ± 1.17 mm/s; p < 0.01).ConclusionThe advantages of ULM over conventional clinical inspections and ultrasound imaging methods for early diagnosis of HN were validated. The quantitative results show that ULM can effectively diagnose HN at the early stage by detecting the blood flow speed changes of interlobular arteries. ULM may promise a reliable technique for early diagnosis of HN in the future.

Background and objectives Outcomes reported in trials in adults with glomerular disease are often selected with minimal patient input, are heterogeneous, and may not be relevant for clinical decision making. The Standardized Outcomes in Nephrology–Glomerular Disease (SONG-GD) initiative aimed to establish a core outcome set to help ensure that outcomes of critical importance to patients, care partners, and clinicians are consistently reported. Design, setting, participants, and measurements We convened two 1.5-hour workshops in Melbourne, Australia, and Washington, DC, United States. Attendees were identified purposively with 50 patients/care partners and 88 health professionals from 19 countries; 51% were female. Patients and care partners were from the United States, Australia, and Canada, and had experience of a glomerular disease with systemic features ( n =9), kidney-limited nephrotic disease ( n =9), or other kidney-limited glomerular disease ( n =8). Attendees reviewed the results of the SONG-GD Delphi survey and aims of the workshop and then discussed potential core outcomes and their implementation in trials among moderated breakout groups of eight to 12 people from diverse backgrounds. Transcripts of discussions were analyzed thematically. Results Three themes were identified that supported the proposed core outcomes: limiting disease progression, stability and control, and ensuring universal relevance ( i.e. , applicable across diverse populations and settings). The fourth theme, preparedness for implementation, included engaging with funders and regulators, establishing reliable and validated measures, and leveraging existing endorsements for patient-reported outcomes. Conclusions Workshop themes demonstrated support for kidney function, disease activity, death, life participation, and cardiovascular disease, and these were established as the core outcomes for trials in adults with glomerular disease. Future work is needed to establish the core measures for each domain, with funders and regulators central to the uptake of the core outcome set in trials.

Background: We hypothesized that the Effective radiation Dose to the Immune Cells (EDIC) in circulating blood is a significant factor for the treatment outcome in patients with locally advanced non-small-cell lung cancer (NSCLC). Methods: This is a secondary study of a phase III trial, NRG/RTOG 0617, in patients with stage III NSCLC treated with radiation-based treatment. The EDIC was computed as equivalent uniform dose to the entire blood based on radiation doses to all blood-containing organs, with consideration of blood flow and fractionation effect. The primary endpoint was overall survival (OS), and the secondary endpoints were progression-free survival (PFS) and local progression-free survival (LPFS). The EDIC–survival relationship was analyzed with consideration of clinical significant factors. Results: A total of 456 patients were eligible. The median EDIC values were 5.6 Gy (range, 2.1–12.2 Gy) and 6.3 Gy (2.1–11.6 Gy) for the low- and high-dose groups, respectively. The EDIC was significantly associated with OS (hazard ratio [HR] = 1.12, p = 0.005) and LPFS (HR = 1.09, p = 0.02) but PFS (HR = 1.05, p = 0.17) after adjustment for tumor dose, gross tumor volume and other factors. OS decreased with an increasing EDIC in a non-linear pattern: the two-year OS decreased first with a slope of 8%/Gy when the EDIC < 6 Gy, remained relatively unchanged when the EDIC was 6–8 Gy, and followed by a further reduction with a slope of 12%/Gy when the EDIC > 8 Gy. Conclusions: The EDIC is a significant independent risk factor for poor OS and LPFS in RTOG 0617 patients with stage III NSCLC, suggesting that radiation dose to circulating immune cells is critical for tumor control. Organ at risk for the immune system should be considered during RT plan.

Abstract Introduction: Multiple studies have demonstrated that diffuse large B-cell lymphoma (DLBCL) can be divided into subgroups based on their biology. However, these biological subgroups overlap clinically. While R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) remains the standard of care for treating patients with DLBCL, predicting which patients will not benefit from such therapy is important so that alternative therapy or clinical trials can be considered. Most of the studies stratifying patients select biomarkers first, then explore how these biomarkers can stratify patients based on outcome. We explored the potential of using machine learning to first group patients with DLBCL based on survival, then isolating the biomarkers necessary for predicting these survival subgroups. Methods: RNA was extracted from tissue paraffin blocks from 379 R-CHOP treated patients with de novo DLBCL, and from 247 patients with extranodal DLBCL. A targeted hybrid capture RNA panel of 1408 genes was used for next generation sequencing (NGS). Sequencing was performed using an Illumina NextSeq 550 System platform. Ten million reads per sample in a single run were required, and the read length was 2 × 150 bp. An expression profile was generated from the sequencing coverage profile of each individual sample using Cufflinks. A machine learning system was developed to classify patients into four groups based on their overall survival. This machine learning approach based on Naïve Bayesian algorithm was also used to discover the relevant subset of genes with which to classify patients into each of the four survival groups. To eliminate the underflow problem commonly associated with the standard Naïve Bayesian classifiers, we applied Geometric Mean Naïve Bayesian (GMNB) as the classifier to predict the survival group for each patient. Results: Using machine learning, patients were first divided into two groups: short survival (S) and long survival (L). To refine this model, we used the same approach and divided the patients in each group into two subgroups, generating four groups: long survival in the long group (LL), short survival in the long group (LS), long survival in the short group (SL), and short survival in the short group (SS). The hazard ratio for this model was 0.174 (confidence interval: 0.120-0.251), and P-value &lt;0.0001. After defining these four groups, a machine learning algorithm was used to discover the biomarkers from the expression data of the 1408 genes from NGS data. To reduce the effects of noise and avoid overfitting, we employed a 12-step cross validation to obtain a robust measure. For an individual gene, a generalized Naïve Bayesian classifier was constructed on the training of one of the 12 subsets and tested on the other 11 testing subsets. This allowed us to limit the prediction process to 60 genes for each separation step. Using the selected biomarkers, we classified the patients in the original set (379 patients) into LL, LS, SL, and SS groups and then evaluated the survival pattern of these groups. As shown in Fig. 1A, the selected biomarkers predicted survival as expected in the overall survival groups prior to biomarker selection. For additional validation of the system, we used the selected biomarkers to classify a completely new set of 247 samples of patients with extranodal DLBCL. As shown in Fig. 1B, these selected biomarkers successfully predicted the overall survival in this group of patients with an HR of 0.530 (confidence interval: 0.234-1.197, P=0.005). This classification correlated with cell of origin classification, TP53 mutation status, MYC expression, and IRF4 expression. However, in a multivariate analysis, only TP53 mutation was independent in predicting prognosis (P=0.005) and age (below or over 60) (P=0.01) along with the survival grouping (P&lt;0.000001). Conclusions: Using a novel machine learning approach with the expression levels of 180 genes, we developed a model that can reliably stratify patients with DLBCL treated with R-CHOP into four survival subgroups. This model can be used to identify patients who may not respond well to R-CHOP to be considered for alternative therapy and clinical trials. Figure 1 Figure 1. Disclosures Hsi: AbbVie Inc, Eli Lilly: Research Funding. Ferreri: Ospedale San Raffaele srl: Patents & Royalties; BMS: Research Funding; Pfizer: Research Funding; Beigene: Research Funding; Hutchison Medipharma: Research Funding; Amgen: Research Funding; Genmab: Research Funding; ADC Therapeutics: Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; PletixaPharm: Membership on an entity's Board of Directors or advisory committees; x Incyte: Membership on an entity's Board of Directors or advisory committees; Adienne: Membership on an entity's Board of Directors or advisory committees. Piris: Millenium/Takeda, EUSA, Jansen, NanoString, Kyowa Kirin, Gilead and Celgene.: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Winter: BMS: Other: Husband: Data and Safety Monitoring Board; Actinium Pharma: Consultancy; Janssen: Other: Husband: Consultancy; Agios: Other: Husband: Consultancy; Gilead: Other: Husband: Consultancy; Epizyme: Other: Husband: Data and Safety Monitoring Board; Ariad/Takeda: Other: Husband: Data and Safety Monitoring Board; Merck: Consultancy, Honoraria, Research Funding; Novartis: Other: Husband: Consultancy, Data and Safety Monitoring Board; Karyopharm (Curio Science): Honoraria.