Publications by authors named "Katherine A Pratte"

19 Publications

  • Page 1 of 1

Multi-omics subtyping pipeline for chronic obstructive pulmonary disease.

PLoS One 2021 25;16(8):e0255337. Epub 2021 Aug 25.

Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America.

Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of mortality in the United States; however, COPD has heterogeneous clinical phenotypes. This is the first large scale attempt which uses transcriptomics, proteomics, and metabolomics (multi-omics) to determine whether there are molecularly defined clusters with distinct clinical phenotypes that may underlie the clinical heterogeneity. Subjects included 3,278 subjects from the COPDGene cohort with at least one of the following profiles: whole blood transcriptomes (2,650 subjects); plasma proteomes (1,013 subjects); and plasma metabolomes (1,136 subjects). 489 subjects had all three contemporaneous -omics profiles. Autoencoder embeddings were performed individually for each -omics dataset. Embeddings underwent subspace clustering using MineClus, either individually by -omics or combined, followed by recursive feature selection based on Support Vector Machines. Clusters were tested for associations with clinical variables. Optimal single -omics clustering typically resulted in two clusters. Although there was overlap for individual -omics cluster membership, each -omics cluster tended to be defined by unique molecular pathways. For example, prominent molecular features of the metabolome-based clustering included sphingomyelin, while key molecular features of the transcriptome-based clusters were related to immune and bacterial responses. We also found that when we integrated the -omics data at a later stage, we identified subtypes that varied based on age, severity of disease, in addition to diffusing capacity of the lungs for carbon monoxide, and precent on atrial fibrillation. In contrast, when we integrated the -omics data at an earlier stage by treating all data sets equally, there were no clinical differences between subtypes. Similar to clinical clustering, which has revealed multiple heterogenous clinical phenotypes, we show that transcriptomics, proteomics, and metabolomics tend to define clusters of COPD patients with different clinical characteristics. Thus, integrating these different -omics data sets affords additional insight into the molecular nature of COPD and its heterogeneity.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0255337PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386883PMC
August 2021

Emphysema Progression and Lung Function Decline Among Angiotensin Converting Enzyme Inhibitors and Angiotensin-Receptor Blockade Users in the COPDGene Cohort.

Chest 2021 May 21. Epub 2021 May 21.

Division of Pulmonary and Critical Care, Johns Hopkins University, Baltimore, MD.

Background: Attenuation of transforming growth factor β by blocking angiotensin II has been shown to reduce emphysema in a murine model. General population studies have demonstrated that the use of angiotensin converting enzyme inhibitors (ACEis) and angiotensin-receptor blockers (ARBs) is associated with reduction of emphysema progression in former smokers and that the use of ACEis is associated with reduction of FEV progression in current smokers.

Research Question: Is use of ACEi and ARB associated with less progression of emphysema and FEV decline among individuals with COPD or baseline emphysema?

Methods: Former and current smokers from the Genetic Epidemiology of COPD Study who attended baseline and 5-year follow-up visits, did not change smoking status, and underwent chest CT imaging were included. Adjusted linear mixed models were used to evaluate progression of adjusted lung density (ALD), percent emphysema (%total lung volume <-950 Hounsfield units [HU]), 15th percentile of the attenuation histogram (attenuation [in HU] below which 15% of voxels are situated plus 1,000 HU), and lung function decline over 5 years between ACEi and ARB users and nonusers in those with spirometry-confirmed COPD, as well as all participants and those with baseline emphysema. Effect modification by smoking status also was investigated.

Results: Over 5 years of follow-up, compared with nonusers, ACEi and ARB users with COPD showed slower ALD progression (adjusted mean difference [aMD], 1.6; 95% CI, 0.34-2.9). Slowed lung function decline was not observed based on phase 1 medication (aMD of FEV % predicted, 0.83; 95% CI, -0.62 to 2.3), but was when analysis was limited to consistent ACEi and ARB users (aMD of FEV % predicted, 1.9; 95% CI, 0.14-3.6). No effect modification by smoking status was found for radiographic outcomes, and the lung function effect was more pronounced in former smokers. Results were similar among participants with baseline emphysema.

Interpretation: Among participants with spirometry-confirmed COPD or baseline emphysema, ACEi and ARB use was associated with slower progression of emphysema and lung function decline.

Trial Registry: ClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.
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http://dx.doi.org/10.1016/j.chest.2021.05.007DOI Listing
May 2021

Plasma Metabolomic Signatures of Chronic Obstructive Pulmonary Disease and the Impact of Genetic Variants on Phenotype-Driven Modules.

Netw Syst Med 2020 Dec 31;3(1):159-181. Epub 2020 Dec 31.

National Jewish Health, Denver, Colorado, USA.

Small studies have recently suggested that there are specific plasma metabolic signatures in chronic obstructive pulmonary disease (COPD), but there have been no large comprehensive study of metabolomic signatures in COPD that also integrate genetic variants. Fresh frozen plasma from 957 non-Hispanic white subjects in COPDGene was used to quantify 995 metabolites with Metabolon's global metabolomics platform. Metabolite associations with five COPD phenotypes (chronic bronchitis, exacerbation frequency, percent emphysema, post-bronchodilator forced expiratory volume at one second [FEV]/forced vital capacity [FVC], and FEV percent predicted) were assessed. A metabolome-wide association study was performed to find genetic associations with metabolite levels. Significantly associated single-nucleotide polymorphisms were tested for replication with independent metabolomic platforms and independent cohorts. COPD phenotype-driven modules were identified in network analysis integrated with genetic associations to assess gene-metabolite-phenotype interactions. Of metabolites tested, 147 (14.8%) were significantly associated with at least 1 COPD phenotype. Associations with airflow obstruction were enriched for diacylglycerols and branched chain amino acids. Genetic associations were observed with 109 (11%) metabolites, 72 (66%) of which replicated in an independent cohort. For 20 metabolites, more than 20% of variance was explained by genetics. A sparse network of COPD phenotype-driven modules was identified, often containing metabolites missed in previous testing. Of the 26 COPD phenotype-driven modules, 6 contained metabolites with significant met-QTLs, although little module variance was explained by genetics. A dysregulation of systemic metabolism was predominantly found in COPD phenotypes characterized by airflow obstruction, where we identified robust heritable effects on individual metabolite abundances. However, network analysis, which increased the statistical power to detect associations missed previously in classic regression analyses, revealed that the genetic influence on COPD phenotype-driven metabolomic modules was modest when compared with clinical and environmental factors.
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http://dx.doi.org/10.1089/nsm.2020.0009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8109053PMC
December 2020

Soluble receptor for advanced glycation end products (sRAGE) as a biomarker of COPD.

Respir Res 2021 Apr 27;22(1):127. Epub 2021 Apr 27.

Research and Development, GlaxoSmithKline, Collegeville, PA, USA.

Background: Soluble receptor for advanced glycation end products (sRAGE) is a proposed emphysema and airflow obstruction biomarker; however, previous publications have shown inconsistent associations and only one study has investigate the association between sRAGE and emphysema. No cohorts have examined the association between sRAGE and progressive decline of lung function. There have also been no evaluation of assay compatibility, receiver operating characteristics, and little examination of the effect of genetic variability in non-white population. This manuscript addresses these deficiencies and introduces novel data from Pittsburgh COPD SCCOR and as well as novel work on airflow obstruction. A meta-analysis is used to quantify sRAGE associations with clinical phenotypes.

Methods: sRAGE was measured in four independent longitudinal cohorts on different analytic assays: COPDGene (n = 1443); SPIROMICS (n = 1623); ECLIPSE (n = 2349); Pittsburgh COPD SCCOR (n = 399). We constructed adjusted linear mixed models to determine associations of sRAGE with baseline and follow up forced expiratory volume at one second (FEV) and emphysema by quantitative high-resolution CT lung density at the 15th percentile (adjusted for total lung capacity).

Results: Lower plasma or serum sRAGE values were associated with a COPD diagnosis (P < 0.001), reduced FEV (P < 0.001), and emphysema severity (P < 0.001). In an inverse-variance weighted meta-analysis, one SD lower log-transformed sRAGE was associated with 105 ± 22 mL lower FEV and 4.14 ± 0.55 g/L lower adjusted lung density. After adjusting for covariates, lower sRAGE at baseline was associated with greater FEV decline and emphysema progression only in the ECLIPSE cohort. Non-Hispanic white subjects carrying the rs2070600 minor allele (A) and non-Hispanic African Americans carrying the rs2071288 minor allele (A) had lower sRAGE measurements compare to those with the major allele, but their emphysema-sRAGE regression slopes were similar.

Conclusions: Lower blood sRAGE is associated with more severe airflow obstruction and emphysema, but associations with progression are inconsistent in the cohorts analyzed. In these cohorts, genotype influenced sRAGE measurements and strengthened variance modelling. Thus, genotype should be included in sRAGE evaluations.
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http://dx.doi.org/10.1186/s12931-021-01686-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8076883PMC
April 2021

Metabolomic Profiling Reveals Sex Specific Associations with Chronic Obstructive Pulmonary Disease and Emphysema.

Metabolites 2021 Mar 11;11(3). Epub 2021 Mar 11.

Division of Medicine, National Jewish Health, Denver, CO 80206, USA.

Susceptibility and progression of lung disease, as well as response to treatment, often differ by sex, yet the metabolic mechanisms driving these sex-specific differences are still poorly understood. Women with chronic obstructive pulmonary disease (COPD) have less emphysema and more small airway disease on average than men, though these differences become less pronounced with more severe airflow limitation. While small studies of targeted metabolites have identified compounds differing by sex and COPD status, the sex-specific effect of COPD on systemic metabolism has yet to be interrogated. Significant sex differences were observed in 9 of the 11 modules identified in COPDGene. Sex-specific associations by COPD status and emphysema were observed in 3 modules for each phenotype. Sex stratified individual metabolite associations with COPD demonstrated male-specific associations in sphingomyelins and female-specific associations in acyl carnitines and phosphatidylethanolamines. There was high preservation of module assignments in SPIROMICS (SubPopulations and InteRmediate Outcome Measures In COPD Study) and similar female-specific shift in acyl carnitines. Several COPD associated metabolites differed by sex. Acyl carnitines and sphingomyelins demonstrate sex-specific abundances and may represent important metabolic signatures of sex differences in COPD. Accurately characterizing the sex-specific molecular differences in COPD is vital for personalized diagnostics and therapeutics.
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http://dx.doi.org/10.3390/metabo11030161DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7999201PMC
March 2021

Sensitization to Implant Components Is Associated with Joint Replacement Failure: Identification and Revision to Nonallergenic Hardware Improves Outcomes.

J Allergy Clin Immunol Pract 2021 Aug 17;9(8):3109-3117.e1. Epub 2021 Mar 17.

Division of Environmental and Occupational Health Sciences, Department of Medicine, National Jewish Health, Denver, Colo; Division of Environmental and Occupational Health, University of Colorado School of Medicine, School of Public Health, Aurora, Colo. Electronic address:

Background: Over 90% of one million annual US joint replacements are highly successful. Nonetheless, 10% do poorly owing to infection or mechanical issues. Many implant components are sensitizers, and sensitization could also contribute to implant failure.

Objective: To determine the prevalence of implant sensitization in joint failure patients, their clinical characteristics, and implant revision outcomes. We hypothesized that sensitized patients would improve when revised with nonallergenic materials.

Methods: We prospectively enrolled 105 joint failure patients referred by orthopedic surgeons who had already excluded infection or mechanical causes. Patients provided informed consent, completed a history and physical examination, patch testing to metals and bone cement, and a nickel lymphocyte proliferation test. A study coordinator was able to contact 64% of patients (n = 67) 9 to 12 months later to evaluate outcomes.

Results: A total of 59% were sensitized to an implant component: 32% to metal and 37% to bone cement. The nickel lymphocyte proliferation test was 60% sensitive and 96% specific in diagnosing nickel sensitization. Most sensitized subjects reported no or uncertain histories of reactions to a specific material. Implant sensitized patients were younger and reported previous eczema, joint itching, and implant loosening. By 9 to 12 months later, most patients with a revised implant (revised) described significant improvement (16 of 22 revised for sensitization [P = .0003] vs 9 of 13 revised without sensitization [P = .047]) compared with patients without implant revision). All revised patients with sensitization used components to which they were not sensitized. Pain (P = .001), swelling (P = .035), and instability (P = .006) were significantly reduced in the revised sensitized group.

Conclusions: Sensitization to implant components is an important cause of unexplained joint replacement failure. Joint revisions based on sensitization information resulted in significant improvements.
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http://dx.doi.org/10.1016/j.jaip.2020.12.068DOI Listing
August 2021

Protein Biomarkers for COPD Outcomes.

Chest 2021 Jun 9;159(6):2244-2253. Epub 2021 Jan 9.

National Jewish Health, Denver; University of Colorado, Anschutz Medical Campus, Aurora, CO.

COPD is a clinically heterogeneous syndrome characterized by injury to airways, airspaces, and lung vasculature and usually caused by tobacco smoke and/or air pollution exposure. COPD is also independently associated with nonpulmonary comorbidities (eg, cardiovascular disease) and malignancies (eg, GI, bladder), suggesting a role for systemic injury. Since not all those with exposure develop COPD, there has been a search for plasma and lung biomarkers that confer increased cross-sectional and longitudinal risk. This search typically focuses on clinically relevant COPD outcomes such as FEV, FEV decline, CT measurements of emphysema, or exacerbation frequency. The rapid advances in omics technology and the molecular phenotyping of COPD cohorts now permit large-scale evaluation of genetic, transcriptomic, proteomic, and metabolic biomarkers. This review focuses on protein biomarkers associated with clinically relevant COPD outcomes. The prototypic COPD protein biomarker is alpha-1 antitrypsin; however, this biomarker only accounts for 1% to 5% of COPD. This article reviews and summarizes the evidence for other validated biomarkers for each COPD outcome, and discusses their advantages, weaknesses, and required regulatory steps to move the biomarker from the bench into clinic. Although we highlight the emergence of many novel biomarkers (eg, fibrinogen, soluble receptor for advanced glycation, surfactant protein D, club cell secretory protein), there is increasing evidence that individual biomarkers only explain a fraction of the increased COPD risk and that multiple biomarker panels are needed to completely explain clinical variation and risk in individuals and populations.
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http://dx.doi.org/10.1016/j.chest.2021.01.004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8213963PMC
June 2021

A Risk Prediction Model for Mortality Among Smokers in the COPDGene® Study.

Chronic Obstr Pulm Dis 2020 Oct;7(4):346-361

University of Pittsburgh, Pittsburgh, Pennsylvania.

Background: Risk factor identification is a proven strategy in advancing treatments and preventive therapy for many chronic conditions. Quantifying the impact of those risk factors on health outcomes can consolidate and focus efforts on individuals with specific high-risk profiles. Using multiple risk factors and longitudinal outcomes in 2 independent cohorts, we developed and validated a risk score model to predict mortality in current and former cigarette smokers.

Methods: We obtained extensive data on current and former smokers from the COPD Genetic Epidemiology (COPDGene) study at enrollment. Based on physician input and model goodness-of-fit measures, a subset of variables was selected to fit final Weibull survival models separately for men and women. Coefficients and predictors were translated into a point system, allowing for easy computation of mortality risk scores and probabilities. We then used the SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) cohort for external validation of our model.

Results: Of 9867 COPDGene participants with standard baseline data, 17.6% died over 10 years of follow-up, and 9074 of these participants had the full set of baseline predictors (standard plus 6-minute walk distance and computed tomography variables) available for full model fits. The average age of participants in the cohort was 60 for both men and women, and the average predicted 10-year mortality risk was 18% for women and 25% for men. Model time-integrated area under the receiver operating characteristic curve statistics demonstrated good predictive model accuracy (0.797 average), validated in the external cohort (0.756 average). Risk of mortality was impacted most by 6-minute walk distance, forced expiratory volume in 1 second and age, for both men and women.

Conclusions: Current and former smokers exhibited a wide range of mortality risk over a 10- year period. Our models can identify higher risk individuals who can be targeted for interventions to reduce risk of mortality, for participants with or without chronic obstructive pulmonary disease (COPD) using current Global initiative for obstructive Lung Disease (GOLD) criteria.
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http://dx.doi.org/10.15326/jcopdf.7.4.2020.0146DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7883903PMC
October 2020

Comparison of Proteomic Assessment Methods in Multiple Cohort Studies.

Proteomics 2020 06;20(12):e1900278

Center for Public Health Genomics, University of Virginia, Charlottesville, VA, 22908.

Novel proteomics platforms, such as the aptamer-based SOMAscan platform, can quantify large numbers of proteins efficiently and cost-effectively and are rapidly growing in popularity. However, comparisons to conventional immunoassays remain underexplored, leaving investigators unsure when cross-assay comparisons are appropriate. The correlation of results from immunoassays with relative protein quantification is explored by SOMAscan. For 63 proteins assessed in two chronic obstructive pulmonary disease (COPD) cohorts, subpopulations and intermediate outcome measures in COPD Study (SPIROMICS), and COPDGene, using myriad rules based medicine multiplex immunoassays and SOMAscan, Spearman correlation coefficients range from -0.13 to 0.97, with a median correlation coefficient of ≈0.5 and consistent results across cohorts. A similar range is observed for immunoassays in the population-based Multi-Ethnic Study of Atherosclerosis and for other assays in COPDGene and SPIROMICS. Comparisons of relative quantification from the antibody-based Olink platform and SOMAscan in a small cohort of myocardial infarction patients also show a wide correlation range. Finally, cis pQTL data, mass spectrometry aptamer confirmation, and other publicly available data are integrated to assess relationships with observed correlations. Correlation between proteomics assays shows a wide range and should be carefully considered when comparing and meta-analyzing proteomics data across assays and studies.
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http://dx.doi.org/10.1002/pmic.201900278DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425176PMC
June 2020

Identifying Protein-metabolite Networks Associated with COPD Phenotypes.

Metabolites 2020 Mar 25;10(4). Epub 2020 Mar 25.

Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.

Chronic obstructive pulmonary disease (COPD) is a disease in which airflow obstruction in the lung makes it difficult for patients to breathe. Although COPD occurs predominantly in smokers, there are still deficits in our understanding of the additional risk factors in smokers. To gain a deeper understanding of the COPD molecular signatures, we used Sparse Multiple Canonical Correlation Network (SmCCNet), a recently developed tool that uses sparse multiple canonical correlation analysis, to integrate proteomic and metabolomic data from the blood of 1008 participants of the COPDGene study to identify novel protein-metabolite networks associated with lung function and emphysema. Our aim was to integrate -omic data through SmCCNet to build interpretable networks that could assist in the discovery of novel biomarkers that may have been overlooked in alternative biomarker discovery methods. We found a protein-metabolite network consisting of 13 proteins and 7 metabolites which had a -0.34 correlation (-value = 2.5 × 10) to lung function. We also found a network of 13 proteins and 10 metabolites that had a -0.27 correlation (-value = 2.6 × 10) to percent emphysema. Protein-metabolite networks can provide additional information on the progression of COPD that complements single biomarker or single -omic analyses.
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http://dx.doi.org/10.3390/metabo10040124DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7241079PMC
March 2020

COPDGene 2019: Redefining the Diagnosis of Chronic Obstructive Pulmonary Disease.

Chronic Obstr Pulm Dis 2019 Nov;6(5):384-399

Northeastern University, Boston, Massachusetts.

Background: Chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality. Present-day diagnostic criteria are largely based solely on spirometric criteria. Accumulating evidence has identified a substantial number of individuals without spirometric evidence of COPD who suffer from respiratory symptoms and/or increased morbidity and mortality. There is a clear need for an expanded definition of COPD that is linked to physiologic, structural (computed tomography [CT]) and clinical evidence of disease. Using data from the COPD Genetic Epidemiology study (COPDGene), we hypothesized that an integrated approach that includes environmental exposure, clinical symptoms, chest CT imaging and spirometry better defines disease and captures the likelihood of progression of respiratory obstruction and mortality.

Methods: Four key disease characteristics - environmental exposure (cigarette smoking), clinical symptoms (dyspnea and/or chronic bronchitis), chest CT imaging abnormalities (emphysema, gas trapping and/or airway wall thickening), and abnormal spirometry - were evaluated in a group of 8784 current and former smokers who were participants in COPDGene Phase 1. Using these 4 disease characteristics, 8 categories of participants were identified and evaluated for odds of spirometric disease progression (FEV > 350 ml loss over 5 years), and the hazard ratio for all-cause mortality was examined.

Results: Using smokers without symptoms, CT imaging abnormalities or airflow obstruction as the reference population, individuals were classified as Possible COPD, Probable COPD and Definite COPD. Current Global initiative for obstructive Lung Disease (GOLD) criteria would diagnose 4062 (46%) of the 8784 study participants with COPD. The proposed COPDGene 2019 diagnostic criteria would add an additional 3144 participants. Under the new criteria, 82% of the 8784 study participants would be diagnosed with Possible, Probable or Definite COPD. These COPD groups showed increased risk of disease progression and mortality. Mortality increased in patients as the number of their COPD characteristics increased, with a maximum hazard ratio for all cause-mortality of 5.18 (95% confidence interval [CI]: 4.15-6.48) in those with all 4 disease characteristics.

Conclusions: A substantial portion of smokers with respiratory symptoms and imaging abnormalities do not manifest spirometric obstruction as defined by population normals. These individuals are at significant risk of death and spirometric disease progression. We propose to redefine the diagnosis of COPD through an integrated approach using environmental exposure, clinical symptoms, CT imaging and spirometric criteria. These expanded criteria offer the potential to stimulate both current and future interventions that could slow or halt disease progression in patients before disability or irreversible lung structural changes develop.
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http://dx.doi.org/10.15326/jcopdf.6.5.2019.0149DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7020846PMC
November 2019

Bronchoalveolar Lavage Fluid from COPD Patients Reveals More Compounds Associated with Disease than Matched Plasma.

Metabolites 2019 Jul 25;9(8). Epub 2019 Jul 25.

School of Medicine, University of Colorado, Aurora, CO 80045, USA.

Smoking causes chronic obstructive pulmonary disease (COPD). Though recent studies identified a COPD metabolomic signature in blood, no large studies examine the metabolome in bronchoalveolar lavage (BAL) fluid, a more direct representation of lung cell metabolism. We performed untargeted liquid chromatography-mass spectrometry (LC-MS) on BAL and matched plasma from 115 subjects from the SPIROMICS cohort. Regression was performed with COPD phenotypes as the outcome and metabolites as the predictor, adjusted for clinical covariates and false discovery rate. Weighted gene co-expression network analysis (WGCNA) grouped metabolites into modules which were then associated with phenotypes. K-means clustering grouped similar subjects. We detected 7939 and 10,561 compounds in BAL and paired plasma samples, respectively. FEV/FVC (Forced Expiratory Volume in One Second/Forced Vital Capacity) ratio, emphysema, FEV % predicted, and COPD exacerbations associated with 1230, 792, eight, and one BAL compounds, respectively. Only two plasma compounds associated with a COPD phenotype (emphysema). Three BAL co-expression modules associated with FEV/FVC and emphysema. K-means BAL metabolomic signature clustering identified two groups, one with more airway obstruction (34% of subjects, median FEV/FVC 0.67), one with less (66% of subjects, median FEV/FVC 0.77; < 2 × 10). Associations between metabolites and COPD phenotypes are more robustly represented in BAL compared to plasma.
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http://dx.doi.org/10.3390/metabo9080157DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724137PMC
July 2019

Regression to Normal Glucose Regulation in American Indians and Alaska Natives of a Diabetes Prevention Program.

Diabetes Care 2019 07 8;42(7):1209-1216. Epub 2019 Jun 8.

Department of Epidemiology, School of Medicine, University of California, Irvine, Irvine, CA

Objective: This study evaluated whether regression from impaired glucose regulation (IGR) to normal glucose regulation (NGR) after 1 year of a lifestyle intervention reduces diabetes risk in American Indians and Alaska Natives (AI/ANs). In addition, we sought to identify predictors for regression to NGR and understand possible mechanisms for the association between NGR and future diabetes risk.

Research Design And Methods: Data from participants enrolled from 2006 to 2009 in the Special Diabetes Program for Indians Diabetes Prevention Program with IGR at baseline and an oral glucose tolerance test at year 1 were analyzed ( = 1,443). Cox regression models were used to estimate the subsequent diabetes risk (year 1 to year 3) by year 1 glucose status. Mediation analysis was used to estimate the proportions of the association between year 1 glycemic status and diabetes risk explained by specific factors.

Results: Those who reverted to NGR at year 1 (38%) had lower diabetes risk than those with sustained IGR (adjusted hazard ratio 0.28, 95% CI 0.12-0.67). The lower risk associated with regression to NGR was explained by both baseline risk factors and differences in weight loss. Metformin use, weight loss, and an increase in exercise were modifiable risk factors associated with higher odds of regression to NGR.

Conclusions: Patients with prediabetes who reverted to NGR had a reduced risk of developing type 2 diabetes over the next 2 years. Both baseline and modifiable risk factors explained the risk reduction associated with NGR.
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http://dx.doi.org/10.2337/dc18-1964DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609959PMC
July 2019

Recruitment and effectiveness by cohort in a case management intervention among American Indians and Alaska Natives with diabetes.

Transl Behav Med 2019 07;9(4):749-758

Department of Epidemiology, University of California Irvine, School of Medicine, Irvine, CA, USA.

In real-world settings, eligible populations and intervention effectiveness for a translational intervention likely vary across time. To determine the optimal strategies for effective large-scale implementation of evidence-based interventions, it is critical to investigate these potential variabilities. The purpose of this study is to evaluate whether patient characteristics and intervention effectiveness differed by year of enrollment in a multiyear evidence-based translational intervention. The Special Diabetes Program for Indians Healthy Heart (SDPI-HH) Demonstration Project is an intensive case management intervention designed to reduce cardiovascular disease risk among American Indians and Alaska Natives with diabetes. SDPI-HH participants recruited from 2006 through 2008 were included. Baseline characteristics were compared by year of enrollment. We also evaluated the differences in improvements in clinical and behavioral risk factors for cardiovascular disease among participants recruited in different years. The baseline characteristics of the three cohorts significantly differed in demographics, diabetes duration, health behaviors, level of motivation, and clinical measures. Improvements in 13 clinical and behavioral outcomes also differed by enrollment year with the 2006 cohort having the greatest number of significant improvements and the highest rates of participation and retention. Further investigation into the ways to modify the intensive case management model to address differences in levels of motivation and participation is warranted to improve the management of chronic disease in Indian health. Given the evolving nature of translational initiatives of this kind, our analysis results highlight the need to understand and adapt during the natural progression of health behavioral interventions.
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http://dx.doi.org/10.1093/tbm/iby068DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7184863PMC
July 2019

Psychosocial Predictors of Weight Loss among American Indian and Alaska Native Participants in a Diabetes Prevention Translational Project.

J Diabetes Res 2016 15;2016:1546939. Epub 2015 Nov 15.

Centers for American Indian and Alaska Native Health, Colorado School of Public Health, University of Colorado Denver, Aurora, CO 80045, USA.

The association of psychosocial factors (psychological distress, coping skills, family support, trauma exposure, and spirituality) with initial weight and weight loss among American Indians and Alaska Natives (AI/ANs) in a diabetes prevention translational project was investigated. Participants (n = 3,135) were confirmed as prediabetic and subsequently enrolled in the Special Diabetes Program for Indians Diabetes Prevention (SDPI-DP) demonstration project implemented at 36 Indian health care programs. Measures were obtained at baseline and after completing a 16-session educational curriculum focusing on weight loss through behavioral changes. At baseline, psychological distress and negative family support were linked to greater weight, whereas cultural spirituality was correlated with lower weight. Furthermore, psychological distress and negative family support predicted less weight loss, and positive family support predicted greater weight loss, over the course of the intervention. These bivariate relationships between psychosocial factors and weight remained statistically significant within a multivariate model, after controlling for sociodemographic characteristics. Conversely, coping skills and trauma exposure were not significantly associated with baseline weight or change in weight. These findings demonstrate the influence of psychosocial factors on weight loss in AI/AN communities and have substantial implications for incorporating adjunctive intervention components.
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http://dx.doi.org/10.1155/2016/1546939DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4662977PMC
October 2016

Impact of targeted health promotion on cardiovascular knowledge among American Indians and Alaska Natives.

Health Educ Res 2013 Jun;28(3):437-49

Centers for American Indian and Alaska Native Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.

The National Heart, Lung, and Blood Institute developed the Honoring the Gift of Heart Health (HGHH) curriculum to promote cardiovascular knowledge and heart-healthy lifestyles among American Indians and Alaska Natives (AI/ANs). Using data from a small randomized trial designed to reduce diabetes and cardiovascular disease (CVD) risk among overweight/obese AI/ANs, we evaluated the impact of an adapted HGHH curriculum on cardiovascular knowledge. We also assessed whether the curriculum was effective across levels of health literacy (defined as the 'capacity to obtain, process and understand basic health information and services needed to make appropriate health decisions'). We examined change in knowledge from baseline to 3 months for two groups: HGHH (N = 89) and control (N = 50). Compared with controls, HGHH participants showed significant improvement in heart attack knowledge and marginally significant improvement in stroke and general CVD knowledge. HGHH participants attending ≥1 class showed significantly greater improvement than controls on all three measures. Although HGHH participants with inadequate health literacy had worse heart attack and stroke knowledge at baseline and 3 months than did participants with adequate skills, the degree of improvement in knowledge did not differ by health literacy level. HGHH appears to improve cardiovascular knowledge among AI/ANs across health literacy levels.
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http://dx.doi.org/10.1093/her/cyt054DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3716215PMC
June 2013

Plasminogen activator inhibitor-1 is associated with coronary artery calcium in Type 1 diabetes.

J Diabetes Complications 2009 Nov-Dec;23(6):387-93. Epub 2008 Sep 2.

Department of Epidemiology, Colorado School of Public Health, University of Colorado Denver, Denver, CO 80262, USA.

Background: Elevated levels of plasminogen activator inhibitor-1 (PAI-1), the major inhibitor of fibrinolysis, is associated with coronary artery disease (CAD). This association may not be independent of factors related to insulin resistance (IR). Patients with Type 1 diabetes mellitus have increased CAD and an increase in sub-clinical CAD which develops earlier in life. It is not known if PAI-1 is associated with sub-clinical CAD in Type 1 diabetes or if this association is independent of IR.

Methods And Results: Type 1 diabetes patients (n=560) and participants without diabetes (n=693) were assessed for coronary artery calcium (CAC), a surrogate for subclinical CAD, by electron-beam computed tomography. PAI-1 was associated with CAC in both Type 1 diabetes (OR=1.32, 95% CI=1.12-1.58) and non-diabetes (OR=1.34, 95% CI=1.13-1.58), after controlling for traditional risk factors not associated with IR. In Type 1 diabetes, the relationship between PAI-1 and CAC was strongest for younger participants (P=.02 for PAI-1-by-age interaction) after controlling for factors related to IR. PAI-1 was positively associated with CAC for Type 1 diabetes participants younger than 45 years of age.

Conclusion: PAI-1 levels are independently related to CAC in younger Type 1 diabetes participants. PAI-1 levels were not independently related to CAC in non-diabetes participants.
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http://dx.doi.org/10.1016/j.jdiacomp.2008.07.002DOI Listing
January 2010
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