8 research outputs found
Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD
Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group
Severe Monkeypox in Hospitalized Patients - United States, August 10-October 10, 2022.
As of October 21, 2022, a total of 27,884 monkeypox cases (confirmed and probable) have been reported in the United States.§ Gay, bisexual, and other men who have sex with men have constituted a majority of cases, and persons with HIV infection and those from racial and ethnic minority groups have been disproportionately affected (1,2). During previous monkeypox outbreaks, severe manifestations of disease and poor outcomes have been reported among persons with HIV infection, particularly those with AIDS (3-5). This report summarizes findings from CDC clinical consultations provided for 57 patients aged ≥18 years who were hospitalized with severe manifestations of monkeypox¶ during August 10-October 10, 2022, and highlights three clinically representative cases. Overall, 47 (82%) patients had HIV infection, four (9%) of whom were receiving antiretroviral therapy (ART) before monkeypox diagnosis. Most patients were male (95%) and 68% were non-Hispanic Black (Black). Overall, 17 (30%) patients received intensive care unit (ICU)-level care, and 12 (21%) have died. As of this report, monkeypox was a cause of death or contributing factor in five of these deaths; six deaths remain under investigation to determine whether monkeypox was a causal or contributing factor; and in one death, monkeypox was not a cause or contributing factor.** Health care providers and public health professionals should be aware that severe morbidity and mortality associated with monkeypox have been observed during the current outbreak in the United States (6,7), particularly among highly immunocompromised persons. Providers should test all sexually active patients with suspected monkeypox for HIV at the time of monkeypox testing unless a patient is already known to have HIV infection. Providers should consider early commencement and extended duration of monkeypox-directed therapy††in highly immunocompromised patients with suspected or laboratory-diagnosed monkeypox.§§ Engaging all persons with HIV in sustained care remains a critical public health priority
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Blood eosinophil count thresholds and exacerbations in patients with chronic obstructive pulmonary disease
BACKGROUND:Eosinophilic airway inflammation in patients with chronic obstructive pulmonary disease (COPD) is associated with exacerbations and responsivity to steroids, suggesting potential shared mechanisms with eosinophilic asthma. However, there is no consistent blood eosinophil count that has been used to define the increased exacerbation risk. OBJECTIVE:We sought to investigate blood eosinophil counts associated with exacerbation risk in patients with COPD. METHODS:Blood eosinophil counts and exacerbation risk were analyzed in patients with moderate-to-severe COPD by using 2 independent studies of former and current smokers with longitudinal data. The Genetic Epidemiology of COPD (COPDGene) study was analyzed for discovery (n = 1,553), and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study was analyzed for validation (n = 1,895). A subset of the ECLIPSE study subjects were used to assess the stability of blood eosinophil counts over time. RESULTS:COPD exacerbation risk increased with higher eosinophil counts. An eosinophil count threshold of 300 cells/μL or greater showed adjusted incidence rate ratios for exacerbations of 1.32 in the COPDGene study (95% CI, 1.10-1.63). The cutoff of 300 cells/μL or greater was validated for prospective risk of exacerbation in the ECLIPSE study, with adjusted incidence rate ratios of 1.22 (95% CI, 1.06-1.41) using 3-year follow-up data. Stratified analysis confirmed that the increased exacerbation risk associated with an eosinophil count of 300 cells/μL or greater was driven by subjects with a history of frequent exacerbations in both the COPDGene and ECLIPSE studies. CONCLUSIONS:Patients with moderate-to-severe COPD and blood eosinophil counts of 300 cells/μL or greater had an increased risk exacerbations in the COPDGene study, which was prospectively validated in the ECLIPSE study
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Disease Progression Modeling in Chronic Obstructive Pulmonary Disease
Rationale: The decades-long progression of chronic obstructive pulmonary disease (COPD) renders identifying different trajectories of disease progression challenging.Objectives: To identify subtypes of patients with COPD with distinct longitudinal progression patterns using a novel machine-learning tool called "Subtype and Stage Inference" (SuStaIn) and to evaluate the utility of SuStaIn for patient stratification in COPD.Methods: We applied SuStaIn to cross-sectional computed tomography imaging markers in 3,698 Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1-4 patients and 3,479 controls from the COPDGene (COPD Genetic Epidemiology) study to identify subtypes of patients with COPD. We confirmed the identified subtypes and progression patterns using ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints) data. We assessed the utility of SuStaIn for patient stratification by comparing SuStaIn subtypes and stages at baseline with longitudinal follow-up data.Measurements and Main Results: We identified two trajectories of disease progression in COPD: a "Tissue→Airway" subtype (n = 2,354, 70.4%), in which small airway dysfunction and emphysema precede large airway wall abnormalities, and an "Airway→Tissue" subtype (n = 988, 29.6%), in which large airway wall abnormalities precede emphysema and small airway dysfunction. Subtypes were reproducible in ECLIPSE. Baseline stage in both subtypes correlated with future FEV1/FVC decline (r = -0.16 [P < 0.001] in the Tissue→Airway group; r = -0.14 [P = 0.011] in the Airway→Tissue group). SuStaIn placed 30% of smokers with normal lung function at elevated stages, suggesting imaging changes consistent with early COPD. Individuals with early changes were 2.5 times more likely to meet COPD diagnostic criteria at follow-up.Conclusions: We demonstrate two distinct patterns of disease progression in COPD using SuStaIn, likely representing different endotypes. One third of healthy smokers have detectable imaging changes, suggesting a new biomarker of "early COPD.