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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.

ImportanceChronic obstructive pulmonary disease (COPD) is often undiagnosed. Although genetic risk plays a significant role in COPD susceptibility, its utility in guiding spirometry testing and identifying undiagnosed cases is unclear.ObjectiveTo determine whether a COPD polygenic risk score (PRS) enhances the identification of undiagnosed COPD beyond a case-finding questionnaire (eg, the Lung Function Questionnaire) using conventional risk factors and respiratory symptoms.Design, Setting, and ParticipantsThis cross-sectional analysis of participants 35 years or older who reported no history of physician-diagnosed COPD was conducted using data from 2 observational studies: the community-based Framingham Heart Study (FHS) and the COPD-enriched Genetic Epidemiology of COPD (COPDGene) study.ExposuresModified Lung Function Questionnaire (mLFQ) scores and COPD PRS.Main Outcomes and MeasuresThe primary outcome was spirometry-defined moderate to severe COPD (forced expiratory volume in the first second of expiration/forced vital capacity [FEV1/FVC] <0.7 and FEV1 [percent predicted] <80%). The performance of logistic models was assessed using the PRS, mLFQ score, and PRS plus mLFQ score for predicting spirometry-defined COPD.ResultsAmong 3385 FHS participants (median age, 52.0 years; 45.9% male) and 4095 COPDGene participants (median age, 56.8 years; 55.5% male) who reported no history of COPD, 160 (4.7%) FHS and 775 (18.9%) COPDGene participants had spirometry-defined COPD. Adding the PRS to the mLFQ score significantly improved the area under the curve from 0.78 to 0.84 (P < .001) in FHS, 0.69 to 0.72 (P = .04) in COPDGene non-Hispanic African American, and 0.75 to 0.78 (P < .001) in COPDGene non-Hispanic White participants. At a risk threshold for spirometry referral of 10%, the addition of the PRS to the mLFQ score correctly reclassified 13.8% (95% CI, 6.6%-21.0%) of COPD cases in FHS, but not in COPDGene.Conclusions and RelevanceA COPD PRS enhances the identification of undiagnosed COPD beyond a conventional case-finding approach in the general population. Further research is needed to assess its impact on COPD diagnosis and outcomes.

The future directions in leveraging real-world evidence (RWE) and real-world data (RWD) in the field of lymphoma, as compared to traditional experimental clinical trials, are poised to significantly impact research methodologies, treatment strategies, and patient care. Current methods of clinical trials involve a well-controlled design and patient selection bias. Integrating RWE and RWD with experimental clinical trials offers a multifaceted approach to understanding lymphoma and enhancing patient outcomes. In this review, we discuss how RWE has helped shape lymphoma clinical trials, and we compare and evaluate evidence obtained from real-world lymphoma studies/databases with that obtained from clinical trials. We also discuss methods for utilizing surrogate endpoints to facilitate clinical trials and expedite drug development. RWE can be leveraged to bridge the gap between data obtained from clinical trial populations and the broader patient population encountered in clinical practice, by highlighting differences in outcomes and the need for effective treatment strategies across diverse patient groups.

Abstract Rationale Although many studies have examined gene expression in lung tissue, the gene regulatory processes underlying emphysema are still not well understood. Finding efficient nonimaging screening methods and disease-modifying therapies has been challenging, but knowledge of the transcriptomic features of emphysema may help in this effort. Objectives Our goals were to identify emphysema-associated biological pathways through transcriptomic analysis of bulk lung tissue, to determine the lung cell types in which these emphysema-associated pathways are altered, and to detect unique and overlapping transcriptomic signatures in blood and lung samples. Methods Using RNA-sequencing data from 446 samples in the Lung Tissue Research Consortium and 3,606 blood samples from the COPDGene study, we examined the transcriptomic features of chest computed tomography–quantified emphysema. We also leveraged publicly available lung single-cell RNA-sequencing data to identify cell types showing chronic obstructive pulmonary disease–associated differential expression of the emphysema pathways found in the bulk analyses. Measurements and Main Results In the bulk lung RNA-sequencing analysis, 1,087 differentially expressed genes and 34 dysregulated pathways were significantly associated with emphysema. We observed alternative splicing of several genes and increased activity in pluripotency and cell barrier function pathways. Lung tissue and blood samples shared differentially expressed genes and biological pathways. Multiple lung cell types displayed dysregulation of epithelial barrier function pathways, and distinct pathway activities were observed among various macrophage subpopulations. Conclusions This study identified emphysema-related changes in gene expression and alternative splicing, cell type–specific dysregulated pathways, and instances of shared pathway dysregulation between blood and lung.

Abstract Rationale Constantly exposed to the external environment and mutagens such as tobacco smoke, human lungs have one of the highest somatic mutation rates among all human organs. However, the relationship of these mutations to lung disease and function is not known. Objectives To identify the prevalence and significance of clonal somatic mutations in chronic lung diseases. Methods We analyzed the clonal somatic mutations from 1,251 samples of normal and diseased noncancerous lung tissue RNA sequencing with paired whole-genome sequencing from the Lung Tissue Research Consortium. We examined the associations of somatic mutations with lung function, disease status, and computationally deconvoluted cell types in two of the most common diseases represented in our dataset, chronic obstructive pulmonary disease (COPD; 29%) and idiopathic pulmonary fibrosis (IPF; 13%). Measurements and Main Results Clonal somatic mutational burden was associated with reduced lung function in both COPD and IPF. We identified an increased prevalence of clonal somatic mutations in individuals with IPF compared with normal control subjects and individuals with COPD independent of age and smoking status. IPF clonal somatic mutations were enriched in disease-related and airway epithelial–expressed genes such as MUC5B in IPF. Patients who were MUC5B risk variant carriers had increased odds of developing somatic mutations of MUC5B that were explained by increased expression of MUC5B. Conclusions Our identification of an increased prevalence of clonal somatic mutation in diseased lung that correlates with airway epithelial gene expression and disease severity highlights for the first time the role of somatic mutational processes in lung disease genetics.

Abstract Rationale In addition to rare genetic variants and the MUC5B locus, common genetic variants contribute to idiopathic pulmonary fibrosis (IPF) risk. The predictive power of common variants outside the MUC5B locus for IPF and interstitial lung abnormalities (ILAs) is unknown. Objectives We tested the predictive value of IPF polygenic risk scores (PRSs) with and without the MUC5B region on IPF, ILA, and ILA progression. Methods We developed PRSs that included (PRS-M5B) and excluded (PRS-NO-M5B) the MUC5B region (500-kb window around rs35705950-T) using an IPF genome-wide association study. We assessed PRS associations with area under the receiver operating characteristic curve (AUC) metrics for IPF, ILA, and ILA progression. Measurements and Main Results We included 14,650 participants (1,970 IPF; 1,068 ILA) from six multi-ancestry population-based and case–control cohorts. In cases excluded from genome-wide association study, the PRS-M5B (odds ratio [OR] per SD of the score, 3.1; P = 7.1 × 10−95) and PRS-NO-M5B (OR per SD, 2.8; P = 2.5 × 10−87) were associated with IPF. Participants in the top PRS-NO-M5B quintile had ∼sevenfold odds for IPF compared with those in the first quintile. A clinical model predicted IPF (AUC, 0.61); rs35705950-T and PRS-NO-M5B demonstrated higher AUCs (0.73 and 0.7, respectively), and adding both genetic predictors to a clinical model yielded the highest performance (AUC, 0.81). The PRS-NO-M5B was associated with ILA (OR, 1.25) and ILA progression (OR, 1.16) in European ancestry participants. Conclusions A common genetic variant risk score complements the MUC5B variant to identify individuals at high risk of interstitial lung abnormalities and pulmonary fibrosis.

Background: ERK5 (extracellular signal-regulated kinase 5) is a dual kinase transcription factor containing an N-terminal kinase domain and a C-terminal transcriptional activation domain. Many ERK5 kinase inhibitors have been developed and tested to treat cancer and inflammatory diseases. However, recent data have raised questions about the role of the catalytic activity of ERK5 in proliferation and inflammation. We aimed to investigate how ERK5 reprograms myeloid cells to the proinflammatory senescent phenotype, subsequently leading to atherosclerosis. Methods: A ERK5 S496A (dephosphorylation mimic) knock in (KI) mouse model was generated using CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat–associated 9), and atherosclerosis was characterized by hypercholesterolemia induction. The plaque phenotyping in homozygous ERK5 S496A KI and wild type (WT) mice was studied using imaging mass cytometry. Bone marrow–derived macrophages were isolated from hypercholesterolemic mice and characterized using RNA sequencing and functional in vitro approaches, including senescence, mitochondria reactive oxygen species, and inflammation assays, as well as by metabolic extracellular flux analysis. Results: We show that atherosclerosis was inhibited in ERK5 S496A KI mice. Furthermore, ERK5 S496 phosphorylation mediates both senescence-associated secretory phenotype and senescence-associated stemness by upregulating AHR (aryl hydrocarbon receptor) in plaque and bone marrow–derived macrophages isolated from hypercholesterolemic mice. We also discovered that ERK5 S496 phosphorylation could induce NRF2 (NFE2-related factor 2) SUMOylation at a novel K518 site to inhibit NRF2 transcriptional activity without altering ERK5 catalytic activity and mediates oxidized LDL (low-density lipoprotein)–induced senescence-associated secretory phenotype. Specific ERK5 kinase inhibitors (AX15836 and XMD8-92) also inhibited ERK5 S496 phosphorylation, suggesting the involvement of ERK5 S496 phosphorylation in the anti-inflammatory effects of these ERK5 kinase inhibitors. Conclusions: We discovered a novel mechanism by which the macrophage ERK5-NRF2 axis develops a unique senescence-associated secretory phenotype/stemness phenotype by upregulating AHR to engender atherogenesis. The finding of senescence-associated stemness phenotype provides a molecular explanation to resolve the paradox of senescence in proliferative plaque by permitting myeloid cells to escape the senescence-induced cell cycle arrest during atherosclerosis formation.

Abstract Privacy protection is a core principle of genomic but not proteomic research. We identified independent single nucleotide polymorphism (SNP) quantitative trait loci (pQTL) from COPDGene and Jackson Heart Study (JHS), calculated continuous protein level genotype probabilities, and then applied a naïve Bayesian approach to match proteomes to genomes for 2,812 independent subjects from COPDGene, JHS, SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) and Multi-Ethnic Study of Atherosclerosis (MESA). We were able to correctly match 90%-95% of proteomes to their correct genome and for 95%-99% we could match the proteome to the 1% most likely genome. The accuracy of matching in subjects with African ancestry was lower (~ 60%) unless training included diverse subjects. With larger profiling (SomaScan 5K) in the Atherosclerosis Risk Communities (ARIC) correct identification was > 99% even in mixed ancestry populations. When serial proteomes are available, the matching algorithm can be used to identify and correct mislabeled samples. This work also demonstrates the importance of including diverse populations in omics research and that large proteomic datasets (> 1,000 proteins) can be accurately linked to a specific genome through pQTL knowledge and should not be considered unidentifiable.

Background: There is a paucity of data regarding the association between radiation exposure of heart substructures and the incidence of major coronary events (MCEs) in patients with esophageal cancer (ESOC) undergoing chemoradiation therapy. We studied radiation dosimetric determinants of MCE risk and measured their impact on patient prognosis using a cohort of ESOC patients treated at a single institution. Methods: Between March 2005 and October 2015, 355 ESOC patients treated with concurrent chemoradiotherapy were identified from a prospectively maintained and institutional-regulatory-board-approved clinical database. Dose-distribution parameters of the whole heart, the atria, the ventricles, the left main coronary artery, and three main coronary arteries were extracted for analysis. Results: Within a median follow-up time of 67 months, 14 patients experienced MCEs at a median of 16 months. The incidence of MCEs was significantly associated with the left anterior descending coronary artery (LAD) receiving ≥30 Gy (V30Gy) (p = 0.048). Patients receiving LAD V30Gy ≥ 10% of volume experienced a higher incidence of MCEs versus the LAD V30Gy < 10% group (p = 0.044). The relative rate of death increased with the left main coronary artery (LMA) mean dose (Gy) (p = 0.002). Furthermore, a mutual promotion effect of hyperlipidemia and RT on MCEs was observed. Conclusion: Radiation dose to coronary substructures is associated with MCEs and overall survival in patients with ESOC. In this study, the doses to these substructures appeared to be better predictors of toxicity outcomes than mean heart dose (MHD) or whole-heart V30Gy. These findings have implications for reducing coronary events through radiation therapy planning.