Publications by authors named "Bowler R"

Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole-genome sequencing (WGS) of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program.

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Background/objectives: Both aging and chronic obstructive pulmonary disease (COPD) are strongly associated with changes in the metabolome; however, it is unknown whether there are common aging/COPD metabolomic signatures and if accelerated aging is associated with COPD.

Methods: Plasma from 5704 subjects from the Genetic Epidemiology of COPD study (COPDGene) and 2449 subjects from Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) were profiled using the Metabolon global metabolomics platform (1013 annotated metabolites). Post-bronchodilator spirometry measures of airflow obstruction (forced expiratory volume at one second (FEV)/forced vital capacity (FVC) < 0.

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Background: Little information is available on iron with diabetes risk among African Americans, a population where both anemia and elevated ferritin are common. We tested whether plasma proteomic measurements of ferritin and transferrin were associated with increased diabetes risk in a cohort of current and former African American (NHB) and Non-Hispanic White (NHW) smokers.

Methods: NHB and NHW participants from the COPDGene study who were free of diabetes (n = 4693) at baseline were followed for incident diabetes.

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Among tobacco-exposed persons with preserved spirometry (TEPS), we previously demonstrated that different lung volume indices, specifically elevated total lung capacity (TLC) versus elevated ratio of functional residual capacity-to-TLC (FRC/TLC), identify different lung disease characteristics in the COPDGene cohort. Determine differential disease characteristics and trajectories associated with the lung volume indices among TEPS in the SPIROMICS cohort. We categorized TEPS (n=814) by tertiles (low, intermediate, high) of TLC or residual volume-to-TLC (RV/TLC) derived from baseline CT images, and then examined clinical and spirometric disease trajectories in mutually exclusive categories of participants with high TLC without high RV/TLC ([TLC]) versus high RV/TLC without high TLC ([RV/TLC]).

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Background: Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear. We aimed to define high-risk COPD subtypes using genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.

Methods: We defined high-risk groups based on PRS and TRS quantiles by maximising differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets.

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Article Synopsis
  • Serum IgG deficiency is linked to increased risks of exacerbations in chronic obstructive pulmonary disease (COPD), but the impact of lower normal range levels is uncertain.
  • A study involving 1,497 smokers analyzed the relationship between serum IgG levels and COPD exacerbations, finding that levels below the 35th percentile (1225 mg/dL) heightened exacerbation risk.
  • Specifically, low levels of IgG1 and IgG2 subclasses were significantly correlated with severe exacerbations, indicating that even mild impairments in IgG can affect disease severity in at-risk individuals.
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  • Studies show that different subgroups (based on sex, race, etc.) experience varying disease courses and outcomes, and current analysis methods fail to consider this diversity.* -
  • The authors propose a new statistical approach called Heterogeneity in Integration and Prediction (HIP) that combines multiple data types while factoring in subgroup differences to identify shared and unique molecular signatures.* -
  • HIP has been applied to investigate COPD, revealing important proteins and genes linked to sex differences in the disease, and offers tools for broader research applications in health disparities.*
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Rationale: Accelerated decline in lung function is associated with incident COPD, hospitalizations and death. However, identifying this trajectory with longitudinal spirometry measurements is challenging in clinical practice.

Objective: To determine whether a proteomic risk score trained on accelerated decline in lung function can assess risk of future respiratory disease and mortality.

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Protein biomarkers are associated with mortality in cardiovascular disease, but their effect on predicting respiratory and all-cause mortality is not clear. We tested whether a protein risk score (protRS) can improve prediction of all-cause mortality over clinical risk factors in smokers. We utilized smoking-enriched (COPDGene, LSC, SPIROMICS) and general population-based (MESA) cohorts with SomaScan proteomic and mortality data.

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  • Genetic studies have highlighted the need for more diverse research on plasma fibrinogen levels, as previous studies largely focused on Europeans, leading to gaps in understanding and missing heritability.
  • By analyzing data from whole-genome sequencing and genotype data from large cohorts, researchers identified 18 genetic loci related to fibrinogen levels, some of which are more common in African populations and include variants that may impact protein function.
  • The study's findings indicate a connection between fibrinogen levels and various health conditions, emphasizing the importance of whole-genome sequencing in discovering genetic factors in diverse populations and enhancing knowledge about fibrinogen regulation.
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  • Researchers investigated blood protein networks in chronic obstructive pulmonary disease (COPD) using data from over 3,000 participants to better understand complex interconnections rather than just individual biomarker changes.
  • They applied advanced techniques to analyze 4,776 proteins, identifying significant networks linked to factors like smoking status and emphysema.
  • The study found both known and new proteins associated with COPD, highlighting the importance of these networks in understanding the disease across different ethnic groups, with some results replicating in another study cohort.
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  • Circulating metabolite levels are indicators of human health and can be influenced by genetic factors; however, most research has focused on European populations.
  • The study utilized metabolomics data from 25,058 diverse individuals, identifying 1,778 gene loci linked to 667 metabolites and providing methods for data analysis and handling.
  • Notably, the research uncovered new genetic associations, including 108 novel gene-metabolite pairs, and highlighted sex differences in metabolism, enhancing the understanding of genetic influences on human health.
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  • Rates of cannabis initiation are rising among teenagers and young adults, with an increase in dual use of cannabis and nicotine.
  • There is limited understanding of the health effects of using both substances, especially concerning high-potency cannabis and its impact on future health outcomes.
  • A survey of 457 young people found that while sole cannabis users showed no significant dietary or activity differences, dual users consumed more unhealthy sugars, potentially raising concerns about metabolic syndrome and cardiovascular disease risks.
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  • The SPIROMICS Study of Early COPD Progression (SOURCE) aims to investigate the biological reasons behind early-stage COPD in younger individuals who smoke, addressing a gap in current medical knowledge that hinders treatment development.
  • The study plans to enroll 649 participants aged 30-55 with a history of smoking, alongside 40 never-smoker controls, to collect comprehensive health data and analyze potential mechanisms of disease progression.
  • SOURCE seeks to use advanced imaging and biospecimen collection methods over three years to enhance understanding of COPD and contribute to better prevention and treatment strategies.
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Rationale: Identification and validation of circulating biomarkers for lung function decline in COPD remains an unmet need.

Objective: Identify prognostic and dynamic plasma protein biomarkers of COPD progression.

Methods: We measured plasma proteins using SomaScan from two COPD-enriched cohorts, the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS) and Genetic Epidemiology of COPD (COPDGene), and one population-based cohort, Multi-Ethnic Study of Atherosclerosis (MESA) Lung.

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Accelerated biological aging has been implicated in the development of interstitial lung disease (ILD) and other diseases of aging but remains poorly understood. To identify plasma proteins that mediate the relationship between chronological age and survival association in patients with ILD. Causal mediation analysis was performed to identify plasma proteins that mediated the chronological age-survival relationship in an idiopathic pulmonary fibrosis discovery cohort.

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Ground-glass opacities (GGOs) in the absence of interstitial lung disease are understudied. To assess the association of GGOs with white blood cells (WBCs) and progression of quantified chest computed tomography emphysema. We analyzed data of participants in the SPIROMICS study (Subpopulations and Intermediate Outcome Measures in COPD Study).

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Rationale: Genetic variants and gene expression predict risk of chronic obstructive pulmonary disease (COPD), but their effect on COPD heterogeneity is unclear.

Objectives: Define high-risk COPD subtypes using both genetics (polygenic risk score, PRS) and blood gene expression (transcriptional risk score, TRS) and assess differences in clinical and molecular characteristics.

Methods: We defined high-risk groups based on PRS and TRS quantiles by maximizing differences in protein biomarkers in a COPDGene training set and identified these groups in COPDGene and ECLIPSE test sets.

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Quantitative interstitial abnormalities (QIAs) are a computed tomography (CT) measure of early parenchymal lung disease associated with worse clinical outcomes, including exercise capacity and symptoms. The presence of pulmonary vasculopathy in QIAs and its role in the QIA-outcome relationship is unknown. To quantify radiographic pulmonary vasculopathy in QIAs and determine whether this vasculopathy mediates the QIA-outcome relationship.

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Study Objectives: Cannabis is a common sleep aid; however, the effects of its use prior to sleep are poorly understood. This study aims to determine the impact of nonmedical whole plant cannabis use 3 hours prior to sleep and measured cannabis metabolites on polysomnogram measures.

Methods: This is a cross-sectional study of 177 healthy adults who provided detailed cannabis use history, underwent a 1-night home sleep test and had measurement of 11 plasma and urinary cannabinoids, quantified using mass spectroscopy, the morning after the home sleep test.

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Article Synopsis
  • Inflammation biomarkers offer crucial insights into the inflammatory processes linked to various diseases, and their sequencing can help reveal the genetic makeup of these traits.
  • A study analyzed 21 inflammation biomarkers from around 38,465 individuals, discovering 22 significant associations across 6 inflammatory traits after considering existing findings.
  • The research combined single-variant and rare variant analyses, identifying additional significant associations and highlighting the complexity and diversity of genetic influences on inflammation traits across different ancestries.
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Mosaic loss of Y (mLOY) is the most common somatic chromosomal alteration detected in human blood. The presence of mLOY is associated with altered blood cell counts and increased risk of Alzheimer's disease, solid tumors, and other age-related diseases. We sought to gain a better understanding of genetic drivers and associated phenotypes of mLOY through analyses of whole genome sequencing of a large set of genetically diverse males from the Trans-Omics for Precision Medicine (TOPMed) program.

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As terabytes of multi-omics data are being generated, there is an ever-increasing need for methods facilitating the integration and interpretation of such data. Current multi-omics integration methods typically output lists, clusters, or subnetworks of molecules related to an outcome. Even with expert domain knowledge, discerning the biological processes involved is a time-consuming activity.

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