Citations

Abstract Inflammatory bowel diseases (IBD), principally Crohn’s disease (CD) and ulcerative colitis (UC), are common chronic disorders involving inflammation and often progressive tissue damage. Genome-wide association studies have mapped many risk signals, but the causal variants, effector genes and relevant cellular contexts remain difficult to resolve, limiting mechanistic interpretation and therapeutic translation. Here we performed a multi-ancestry GWAS meta-analysis of 125,992 individuals with IBD and more than 1.2 million controls, identifying 619 independent association signals (374 novel) at 420 IBD regions that account for 77–80% of SNP-based heritability. Fine-mapping resolved 81 high-confidence variants, 41 not previously reported. Although most signals were shared between CD and UC, 39% showed IBD subtype specificity, with UC signals showing stronger enrichment in functional annotations from intestinal epithelial, secretory and enteroendocrine cells, and CD showing stronger genetic correlations with circulating inflammatory biomarkers, including C-reactive protein and glycoprotein acetylation. Latent causal modelling supported a causal effect of decreased high-density lipoprotein on CD risk. By integrating bulk and single-cell eQTL and pQTL resources using colocalisation and Mendelian randomisation, together with coding-variant evidence from exome sequencing, we prioritised 664 candidate effector genes across 341 signals, including 390 newly implicated IBD genes, revealing new biological mechanisms and candidate therapeutic targets supported by human genetics.

Abstract Introduction Sepsis, a dysregulated immune response to infection, accounts for nearly 11 million deaths worldwide each year and remains a major cause of hospital mortality. The absence of precision diagnostics limits efforts to characterize immune dynamics and predict clinical outcomes. We evaluated whether liquid biopsies collected at ICU admission could provide insight into sepsis biology and enable precision diagnostics. Methods We applied cell-free RNA (cfRNA) liquid biopsies as a noninvasive method to highlight signaling networks, identify tissue-specific injury, and predict immune exhaustion. We collected serial samples throughout hospitalization from a cohort of 100 patients admitted with likely sepsis to a medical ICU. Comprehensive clinical data, including inpatient laboratory values and key outcome measures such as survival and ventilator-free days, were curated. Circulating cfRNA was isolated and purified from these samples and prepared for sequencing. We generated data from 254 samples at a minimum sequencing depth of 30x. We then designed a novel deep-learning computational method to enable deconvolution to better analyze and interpret these data. Results In our cohort, a total of 84 patients were adjudicated to have sepsis by the Sepsis-3 criteria, and 25 patients died within 90 days. Differential analysis was performed comparing circulating cfRNA in these septic patients to that of healthy controls, stratified by mortality along with specified subgroups including shock on admission, ventilator dependence, and preexisting immunosuppression. We identified multiple differentially expressed transcripts between septic patients and healthy controls, with significant alterations in signaling cascades associated with mitochondrial signaling, including alterations in oxidative phosphorylation and fatty acid metabolism. Using defined ligand-receptor interaction databases, we identified key pathways associated with immune and endothelial dysfunction in sepsis. Specifically, our analysis identified numerous alterations in CXCL8 (IL-8)-associated signaling cascades (engaging CXCR1, CXCR2, SDC1-3, and ACKR). Our analyses also highlighted key tissue factor pathway inhibitor (TFPI)-associated signaling via interactions with tissue factor and low-density lipoprotein receptor-related protein 1 (LRP1). These analyses are corroborated by our new deep-learning augmented approach to deconvolution, where we demonstrate the identification of rare tissue- and cell-specific signals that are associated with increased mortality in our cohort. Conclusion Liquid biopsy approaches such as cfRNA profiling can provide insight into mechanisms underlying sepsis and may uncover underlying drivers of endothelial dysfunction. These findings support ongoing efforts to develop liquid biopsy-based diagnostics and personalized therapeutic strategies for patients at high risk for sepsis and related mortality. This abstract is funded by: NIH

Abstract Rationale Despite its effectiveness at improving outcomes in patients with COPD, pulmonary rehabilitation (PR) attrition rates are high, often exceeding 50%. Fully remote programs, like home-based PR (HBPR), face additional challenges engaging patients in real-world settings. With the growing adoption of wearables, sensor-derived behavioral measures, like sleep patterns, may identify patients most likely to benefit from remote PR. This study evaluated whether incorporating baseline sleep measures from a wrist-worn activity monitor in machine learning (ML) models improved the prediction of 12-week engagement with HBPR in patients with COPD. Methods Among participants (n = 124), the following sleep measures were collected for 1 week before HBPR: sleep duration (min), standard deviation of sleep duration, wake-after-sleep-onset (WASO) (min), standard deviation of WASO, number of awakenings, length of awakenings (min), activity counts, movement index, movement fragmentation index, and sleep fragmentation index. Sleep measures were processed (1) using a previously validated Tudor-Locke algorithm and (2) applying partial least squares-discriminant analysis (PLS-DA) to generate a single latent variable (Composite Sleep Health Score) for inclusion in models. Engagement was defined as completion of one or more recommended activities per week for the full program duration (12 weeks). To determine if the inclusion of objective sleep measures improved the prediction of HBPR engagement, nested model comparisons for parametric (logistic regression and SVM) and non-parametric (decision tree and naïve bayes) ML models were performed. A sensitivity analysis (SA) replaced the Composite Sleep Health Score with sleep regularity (duration and WASO) measures only. Results In models adjusted for age, sex, Charlson Comorbidity Index, current smoker status, modified Medical Research Council (mMRC), and forced expiratory volume in 1 second (FEV1), the inclusion of the Composite Sleep Health Score significantly improved the prediction of 12-week engagement only in SVM models (AUC 0.755; p = 0.007). Specificity (18.2%) and accuracy (68.5%) also improved by 27.3% and 7.3%, respectively. The Composite Sleep Health Score and mMRC scores ranked most frequently as the variables of highest importance. Identical trends were observed in the SA. Conclusion Although preliminary, these findings support additional investigation into the use of wearable-derived sleep measures to improve screening for HBPR eligibility, identifying patients who will clinically benefit from fully remote PR. Building on these primary findings, future researchers should carefully select variables for model inclusion and initiate new hypotheses elucidating the link between objective sleep measures and HBPR outcomes in COPD patients. This abstract is funded by: NIH R56 HL173214, NIH R01 HL140486, and the Robert D. and Patricia E. Kern Center for the Science of Health Delivery

Abstract Rationale Lymphangioleiomyomatosis (LAM) is a rare, progressive, cystic lung disease affecting women. Sirolimus has been shown to stabilize lung function in women with LAM, but real-world data on long-term safety and efficacy are limited. Methods The NIH Multicenter Safety and Durability of Sirolimus for LAM (MIDAS, NCT02432560) observational registry was launched in 2015. All adult (≥18 years) women with LAM (treated or untreated) were eligible to enroll at any of the 20 U.S. sites and followed longitudinally with serial assessments of lung function, health-related quality of life, and treatment related adverse event (TRAEs). Baseline cohort characteristics and TRAEs are summarized using descriptive analyses. Marginal structural models (MSMs) with inverse probability of treatment weighting estimated the causal effect of sirolimus on annualized forced expiratory volume in one-second (FEV1) decline, adjusting for age at LAM diagnosis, prior treatment with sirolimus, menopausal status, race, presence of angiomyolipomas, supplemental oxygen use; time-varying covariates included diffusing capacity for carbon monoxide (DLCO) and serum vascular endothelial growth factor-D (VEGF-D) levels. Results Longitudinal data was available in 350 LAM patients, most of whom (246, 70.3%) had sporadic LAM. The median age at the baseline pulmonary function test (PFT) measurement was 46 years (range: 19 - 74) and the median (IQR) number of serial PFTs obtained per patient was 3 (1 - 5). The average follow-up duration per patient was 2.8 years. Over half of the patients (196, 56%) were treated with sirolimus during the MIDAS observation period for a median (IQR) treatment duration of 4.9 (2.4 - 7.5) years. MSM analysis demonstrated that sirolimus treatment was durably effective and reduced FEV₁ decline by 74.36 mL/year (95% CI: 15.87 - 132.85) compared with no treatment (-85.31 mL/year for the untreated group vs. -10.95 mL/year for the treated group, p = 0.01). Sirolimus was generally well tolerated; treatment interruption ≥3 months was observed in 38 (19.4%) of the 196 sirolimus treated patients. Logistic regression analysis showed that higher levels of FEV1 (odds ratio: OR = 3.12 [1.45 - 7.11], p = 0.005), VEGF-D (OR = 1.0007 [1.0004 - 1.001], p < 0.001), and DLCO (OR = 1.023 [1.0053 - 1.0413, p = 0.01]), were associated with treatment interruption. Conclusions In the MIDAS cohort, sirolimus treatment resulted in durable stabilization of lung function with a favorable safety profile over a 5-year period. These real-world data support sirolimus as a chronic suppressive therapy for LAM, demonstrating durable efficacy in slowing lung disease progression and tolerability with long-term use. This abstract is funded by: National Institutes of Health

Abstract Rationale Type-1 inflammation in asthma leads to significant airway level changes independent of Type-2 inflammation and may underlie the severity seen in combined Type1/2 high disease. As IFNs can cause airway epithelial injury and impaired repair, we applied a novel interpretable machine learning algorithm, SLIDE, to analyze the transcriptome of airway epithelial brushings of mild-moderate (MMA) and severe asthma (SA) participants in the Immune Mechanisms in Severe Asthma (IMSA) cohort to identify latent/hidden factors of disease that associate with disease severity. Methods The expression of genes identified by SLIDE as part of a co-expression program was assessed in the full IMSA cohort by severity and in an independent cohort of the NHLBI Severe Asthma Research Program (SARP). We also examined associations of these genes with clinical asthma outcomes in both cohorts. Results SLIDE identified aberrant increased expression of membrane-tethered mucin genes, MUC1 and MUC4. MUC1 appeared in each of 5 significant latent factors associated with greater severity and MUC4 in 2/5. Standard DGE analysis also identified the gene CEACAM5 as a predictor of severity. Pathway analysis of latent factor genes revealed airway keratinization which may contribute to airway remodeling and worsening obstruction over time. Expression of MUC1, MUC4, and CEACAM5 were increased in SA compared to HC in both the full IMSA and separate SARP cohorts (p < 0.001 for all genes in both cohorts). Expression in MMA was consistently lower than in SA in both cohorts, reaching significance in IMSA (p < 0.01) but not consistently in SARP (MUC1 p = 0.04, MUC4 p = 0.27, CEACAM5 p = 0.27). Protein analysis of endobronchial biopsies by immunofluorescence staining showed a trend towards increased MUC1 protein content with evidence of secretion. MUC1, MUC4 and CEACAM5 were negatively correlated with FEV1 % predicted in both cohorts (IMSA: MUC1 r=-0.47, p < 0.01, MUC4 r=-0.47, p < 0.01, CEACAM5 r=-0.62, p < 0.01; SARP: MUC1 r=-0.19, p = 0.05, MUC4 r=-0.29, p < 0.01, CEACAM5 r=-0.51, p < 0.01). All three genes positively correlated with prospective exacerbations in both cohorts (IMSA: MUC1 r = 0.345, p = 0.01, MUC4 r = 0.216, p = 0.08, CEACAM5 r = 0.368, p < 0.01; SARP: MUC1 r = 0.22, p = 0.02, MUC4 r = 0.32, p < 0.01, CEACAM5 r = 0.38, p < 0.01). Conclusions The expression of MUC1, MUC4 and CEACAM5 increased with asthma severity in the airway epithelium and correlated with both prospective exacerbations and obstruction. As pathway analysis of genes in the significant latent factors were associated with airway keratinization aberrant expression of these mucins (with known signaling functions) may contribute to maladaptive repair and airway remodeling that drives obstruction over time, contributing to worse asthma outcomes. This abstract is funded by: NIH

Abstract Rationale The activity of fucosyltransferase 2 (FUT2) determines if mucin glycan structures in epithelial mucus include histo-blood group antigens (HBGAs). People with active FUT2 express HBGAs in epithelial mucus secretions and are terms “secretors”, while non-secretors lack HBGAs in their secretions because they have a FUT2 genotype that inactivates the glycosyl transferase. Prior research suggests that secretors who are blood type O (type O secretors) are susceptible to asthma exacerbations1 and that FUT2 knockout mice (functional non-secretors) are protected from mucus plugging in allergen challenge models2,3. We set out here to determine if secretor status influences mucus plug prevalence in asthma and to confirm if type O secretors are susceptible to asthma exacerbations. Methods We determined secretor status in asthma participants from the Severe Asthma Research Program-3 (SARP-3) cohort (N = 507) in two ways, a specific fucose lectin binding assay in sputum and FUT2 genotyping. Blood group type was determined using ABO genotyping. We analyzed mucus plug segment scores, asthma exacerbations rates and other clinical and biological features in patients stratified by secretor status and blood type (non-secretors, type O secretors, and non-type O secretors). Results Secretor status determined by lectin binding in sputum was strongly concordant with genotypic analysis. Within the SARP-3 cohort, 26.2% were non-secretors, 32.3% type were O secretors, and 41.4% were non-type O secretors. Mucus plug segment scores, annualized asthma exacerbation rates, and other measures of asthma severity were similar in non-secretors, type O secretors, and non-type O secretors (Table). Although type O secretors had increased values for fractional exhaled nitric oxide (FeNO) and higher expression of type 2 gene network genes in their sputum cells, measures of sputum eosinophil inflammation were not higher in this subgroup (Table). Conclusion Secretor status does not influence the prevalence of mucus plugging in asthma patients, and we did not confirm a prior report that type O secretors have an increased risk of asthma exacerbation. Although type O secretors have modestly increased FeNO levels and increased expression of type 2 immune genes in their sputum, it is not clear if this is a biologically important signal. 1. Innes et al. AJRCCM; 2011. 2. Saku et al. JACI; 2019. 3. Hara et al. AJRCMB; 2025 This abstract is funded by: The study was supported by the National Institutes of Health grants R01 HL080414 (JVF), P01 HL107202 (JVF), R01 HL164787 (JVF), U10 HL109172 (EI), U10 HL109152 (SEW), U10 HL109257 (MC), U10 HL109250 (SCE), U10 HL109146 (JVF), U10 HL109164 (ERB), U01 HL146002 (BDL), U10 HL109086 (DTM) and Sandler Asthma Basic Research Center at UCSF (JVF). The following companies provided financial support for study activities at the Coordinating and Clinical Centers beyond the third year of patient follow-up: AstraZeneca, Boehringer-Ingelheim, Genentech, GlaxoSmithKline, Sanofi–Genzyme Regeneron, and Teva. These companies had no role in study design or data analysis, and the only restriction on the funds was that they be used to support the SARP initiative.

ABSTRACT Novel β-lactam/β-lactamase inhibitors (βL/βLIs) are important therapies for carbapenem-resistant Pseudomonas aeruginosa (CRPA). However, the global extent of resistance to these agents and the impact of resistance on patient outcomes are unclear. We therefore evaluated patients with CRPA isolates at 35 hospitals (nine countries) from December 2018 to November 2019. Antimicrobial susceptibility testing was performed at a central laboratory by agar dilution for ceftolozane-tazobactam (C/T) and ceftazidime-avibactam (CZA) and by broth microdilution for imipenem-relebactam (I/R). Characteristics and outcomes, including desirability of outcome rankings (DOOR), were compared between patients infected with isolates not susceptible vs susceptible to each agent. Of 800 CRPA isolates, susceptibility to C/T, CZA, and I/R was 69%, 67%, and 33%, respectively. USA isolates ( n = 526) were more frequently susceptible to these agents than isolates from other countries ( n = 274; C/T: 83% vs 42%; CZA: 77% vs 47%; I/R: 37% vs 23%; P < 0.001 for each comparison) and isolates with carbapenemases ( n = 157) were less frequently susceptible than isolates without carbapenemases ( n = 643; C/T: 7% vs 84%; CZA: 24% vs 77%; I/R: 6% vs 39%; P < 0.001 for each comparison). Thirty-day mortality and DOOR were similar overall in patients infected with isolates not susceptible vs susceptible to each βL/βLI. However, the adjusted probability of a better DOOR outcome for a randomly selected patient with bacteremia due to a C/T-not susceptible vs -susceptible isolate was 38.2% (95% confidence interval, 25.6%–52.7%). Resistance to novel βL/βLIs, especially I/R, is common in CRPA, particularly outside the USA and in carbapenemase-producing isolates. Additional treatment options are needed for CRPA infections.

Abstract The growing availability of large-scale biomarker datasets has allowed data-driven methods to characterize Alzheimer’s disease biological heterogeneity. However, most prior studies have focused on cohorts of late-onset amnestic cases, leaving early-onset Alzheimer’s disease underexplored. We aimed to characterize tau-PET-based subtypes through a robust data-driven approach in the Longitudinal Early-Onset Alzheimer’s Disease Study. Baseline [18F]Flortaucipir PET scans from 365 amyloid-PET-positive participants with sporadic early-onset Alzheimer’s disease were quantified in the left and right medial temporal, lateral temporal, occipital, parietal, and frontal cortices. Tau PET values were z-scored against 85 amyloid-PET-negative cognitively normal age-matched participants and fitted into Subtype and Stage Inference (SuStaIn)—an unsupervised clustering algorithm that simultaneously models subtypes and progression from cross-sectional data. The derived subtypes were subsequently characterized by baseline and longitudinal clinical, cognitive, MRI, tau and amyloid PET features. We identified three tau-PET-based subtypes: on average, Subtype 1/Typical (n = 144, 40%) showed a predominant bilateral temporoparietal pattern typical of Alzheimer’s disease. Subtype 2/Left temporal (n = 111, 31%) showed predominant left temporal binding. Subtype 3/Posterior (n = 104, 29%) showed early and permeating occipitoparietal involvement. Subtypes did not differ in demographics or global amyloid burden, but were relatively more enriched for specific clinical presentations: S1/Typical for amnestic presentations, S2/Left Temporal for primary progressive aphasia, and S3/Posterior for posterior cortical atrophy. Baseline tau PET subtypes aligned with cortical atrophy patterns and domain-specific cognitive impairment. When follow-up tau PET scans were fitted to SuStaIn trained on baseline data, 85.6% (n = 172/201) of participants retained the same subtype classification, indicating subtype temporal stability, and progressed within subtypes by 0.56 ± 0.70 SuStaIn stage/year. Longitudinal voxel-wise linear mixed-effects modelling revealed tau accumulation patterns for each subtype in regions relatively spared at baseline: occipital lobe accumulation predominated in S1/Typical, bilateral frontal and right temporal in S2/Left Temporal, and bilateral frontotemporal lobes in S3/Posterior. All subtypes showed longitudinal increases in Clinical Dementia Rating-Sum of Boxes, but with slower worsening in S3/Posterior compared with the other subtypes. Our findings reveal robust subtypes in sporadic early-onset Alzheimer’s disease characterized by distinct spatiotemporal tau patterns that parallel differences in clinical presentations and trajectories of neurodegeneration. These subtypes extend beyond traditional clinical syndromes and support a more nuanced framework for individualized prognosis and care. Incorporating tau PET subtyping into clinical trial design could enable more targeted therapeutic approaches for this younger population.

Abstract Background Older adults remain underrepresented in prospective trials of immunotherapy for advanced lung cancer. To estimate pembrolizumab adverse events, we conducted a multicenter, nonrandomized, open-label phase 2 trial of oncologist-choice first-line pembrolizumab with or without chemotherapy for older adults with advanced lung adenocarcinoma. Methods Alliance for Clinical Trials in Oncology A171901 enrolled patients aged 70 years and older with stage IV or recurrent lung adenocarcinoma starting oncologist’s choice of first-line pembrolizumab with or without carboplatin and pemetrexed. The primary endpoint was the proportion of patients experiencing a solicited grade 3 or greater adverse event within 6 months. Secondary endpoints included overall survival, quality of life, and association of a geriatric assessment toxicity risk score with severe adverse events. Results Among 95 evaluable patients, 43 (45.3%) received pembrolizumab and 52 (54.7%) received pembrolizumab plus chemotherapy. Median age was 77 years (range = 70-92 years); 11.6% had an E Performance Status of 2 or higher. During 6 months of treatment, 25.6% (95% CI = 13.5% to 41.2%) experienced a solicited grade 3 or greater adverse event in the monotherapy group and 42.3% (95% CI = 28.7% to 56.8%) in the combination group. Median overall survival was 16.4 months (95% CI = 10.1 to not estimable) with monotherapy and 29.9 months (95% CI = 16.4 to not estimable) with combination therapy. Quality of life worsened during treatment. The geriatric assessment toxicity risk score was not associated with severe adverse events with pembrolizumab with or without chemotherapy. Conclusions Older adults with advanced lung adenocarcinoma receiving pembrolizumab with or without chemotherapy had comparable adverse event rates to those in prior registration trials that excluded medically frail patients. These findings can inform shared decision making and support inclusion of older adults in future trials. Clinical Trial NCT04533451 (https://clinicaltrials.gov/study/NCT04533451)

Augmented cardiovascular responses to spontaneous nocturnal arousals were previously shown in chronic short-sleeping adults, without known sex differences. Sustained 4-h sleep restriction produced a sex-dependent alteration in heart rate responses to arousals and resulted in a prolonged reduction in postarousal pulse transit time in females only. These findings yield the first sex-specific characterization of nocturnal cardiovascular responses to spontaneous arousals following sleep restriction, and may place females at greater sleep truncation-related cardiovascular disease risk.