Publications by authors named "Pallavi P Balte"

Rationale: Chronic lung diseases are associated with increased risk of mortality due to coronary heart disease (CHD). Nonetheless, the population attributable fraction (PAF) of lung function impairment relative to other established cardiovascular risk factors is unclear.

Objective: To evaluate the PAF of low lung function for CHD mortality Methods: We harmonized and pooled lung function and clinical data across 8 US general population cohorts.

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Importance: Persistent symptoms and disability following SARS-CoV-2 infection, known as post-COVID-19 condition or "long COVID," are frequently reported and pose a substantial personal and societal burden.

Objective: To determine time to recovery following SARS-CoV-2 infection and identify factors associated with recovery by 90 days.

Design, Setting, And Participants: For this prospective cohort study, standardized ascertainment of SARS-CoV-2 infection was conducted starting in April 1, 2020, across 14 ongoing National Institutes of Health-funded cohorts that have enrolled and followed participants since 1971.

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Article Synopsis
  • Familial hypercholesterolemia (FH) is a genetic condition linked to high LDL cholesterol levels and increased risk of early coronary heart disease (CHD), though its effects on CHD in those with moderate LDL-C levels are not fully understood.
  • * This study evaluated the CHD risk from FH variants in individuals with both moderately and severely elevated LDL-C levels and estimated the additional deaths from CHD related to FH in U.S. adults.
  • * Among 21,426 participants, those with FH variants had significantly higher rates of developing CHD, with hazard ratios of 2.9 for those with moderately elevated LDL-C and 2.6 for those with severely elevated LDL-C.
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Background: Treatment and preventative advances for chronic obstructive pulmonary disease (COPD) have been slow due, in part, to limited subphenotypes. We tested if unsupervised machine learning on CT images would discover CT emphysema subtypes with distinct characteristics, prognoses and genetic associations.

Methods: New CT emphysema subtypes were identified by unsupervised machine learning on only the texture and location of emphysematous regions on CT scans from 2853 participants in the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS), a COPD case-control study, followed by data reduction.

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Aims: The aim is to evaluate associations of lung function impairment with risk of incident heart failure (HF).

Methods And Results: Data were pooled across eight US population-based cohorts that enrolled participants from 1987 to 2004. Participants with self-reported baseline cardiovascular disease were excluded.

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While polygenic risk scores (PRSs) enable early identification of genetic risk for chronic obstructive pulmonary disease (COPD), predictive performance is limited when the discovery and target populations are not well matched. Hypothesizing that the biological mechanisms of disease are shared across ancestry groups, we introduce a PrediXcan-derived polygenic transcriptome risk score (PTRS) to improve cross-ethnic portability of risk prediction. We constructed the PTRS using summary statistics from application of PrediXcan on large-scale GWASs of lung function (forced expiratory volume in 1 s [FEV] and its ratio to forced vital capacity [FEV/FVC]) in the UK Biobank.

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The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults comprising 14 established US prospective cohort studies. Starting as early as 1971, investigators in the C4R cohort studies have collected data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R links this pre-coronavirus disease 2019 (COVID-19) phenotyping to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and postacute COVID-related illness.

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Early detection of chronic obstructive pulmonary disease (COPD) is a public health priority. Airflow obstruction is the single most important risk factor for adverse COPD outcomes, but spirometry is not routinely recommended for screening. To describe the burden of subclinical airflow obstruction (SAO) and to develop a probability score for SAO to inform potential detection and prevention programs.

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Pulmonary emphysema overlaps considerably with chronic obstructive pulmonary disease (COPD), and is traditionally subcategorized into three subtypes previously identified on autopsy. Unsupervised learning of emphysema subtypes on computed tomography (CT) opens the way to new definitions of emphysema subtypes and eliminates the need of thorough manual labeling. However, CT-based emphysema subtypes have been limited to texture-based patterns without considering spatial location.

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The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) is a national prospective study of adults at risk for coronavirus disease 2019 (COVID-19) comprising 14 established United States (US) prospective cohort studies. For decades, C4R cohorts have collected extensive data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health. C4R will link this pre-COVID phenotyping to information on SARS-CoV-2 infection and acute and post-acute COVID-related illness.

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Chronic obstructive pulmonary disease (COPD), diagnosed by reduced lung function, is a leading cause of morbidity and mortality. We performed whole genome sequence (WGS) analysis of lung function and COPD in a multi-ethnic sample of 11,497 participants from population- and family-based studies, and 8499 individuals from COPD-enriched studies in the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. We identify at genome-wide significance 10 known GWAS loci and 22 distinct, previously unreported loci, including two common variant signals from stratified analysis of African Americans.

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Importance: Chronic bronchitis has been associated with cigarette smoking as well as with e-cigarette use among young adults, but the association of chronic bronchitis in persons without airflow obstruction or clinical asthma, described as nonobstructive chronic bronchitis, with respiratory health outcomes remains uncertain.

Objective: To assess whether nonobstructive chronic bronchitis is associated with adverse respiratory health outcomes in adult ever smokers and never smokers.

Design, Setting, And Participants: This prospective cohort study included 22 325 adults without initial airflow obstruction (defined as the ratio of forced expiratory volume in the first second [FEV1] to forced vital capacity [FVC] of <0.

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Background: Former smokers now outnumber current smokers in many developed countries, and current smokers are smoking fewer cigarettes per day. Some data suggest that lung function decline normalises with smoking cessation; however, mechanistic studies suggest that lung function decline could continue. We hypothesised that former smokers and low-intensity current smokers have accelerated lung function decline compared with never-smokers, including among those without prevalent lung disease.

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Background: Blood pressure (BP) and cholesterol are major modifiable risk factors for cardiovascular disease (CVD), but effects of exposures during young adulthood on later life CVD risk have not been well quantified.

Objective: The authors sought to evaluate the independent associations between young adult exposures to risk factors and later life CVD risk, accounting for later life exposures.

Methods: The authors pooled data from 6 U.

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Importance: According to numerous current guidelines, the diagnosis of chronic obstructive pulmonary disease (COPD) requires a ratio of the forced expiratory volume in the first second to the forced vital capacity (FEV1:FVC) of less than 0.70, yet this fixed threshold is based on expert opinion and remains controversial.

Objective: To determine the discriminative accuracy of various FEV1:FVC fixed thresholds for predicting COPD-related hospitalization and mortality.

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Emphysema quantification and sub-typing is actively studied on cohorts of full-lung high-resolution CT (HRCT) scans, with promising results. Transfer of quantification and classification tools to cardiac CT scans, which involve 70% of the lungs, is challenging due to lower image resolution and degradation of textural patterns. In this study, we propose an original deep-learning domain-adaptation framework to use a pre-existing dictionary of lung texture patterns (LTP), learned on gold-standard full-lung HRCT scans, to label emphysema regions on cardiac CT scans.

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Rationale: Chronic lower respiratory diseases (CLRDs), including chronic obstructive pulmonary disease (COPD) and asthma, are the fourth leading cause of death. Prior studies suggest that albuminuria, a biomarker of endothelial injury, is increased in patients with COPD.

Objectives: To test whether albuminuria was associated with lung function decline and incident CLRDs.

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Chronic lower respiratory diseases (CLRDs) are the fourth leading cause of death in the United States. To support investigations into CLRD risk determinants and new approaches to primary prevention, we aimed to harmonize and pool respiratory data from US general population-based cohorts. Data were obtained from prospective cohorts that performed prebronchodilator spirometry and were harmonized following 2005 ATS/ERS standards.

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Unsupervised discovery of pulmonary emphysema subtypes offers the potential for new definitions of emphysema on lung computed tomography (CT) that go beyond the standard subtypes identified on autopsy. Emphysema subtypes can be defined on CT as a variety of textures with certain spatial prevalence. However, most existing approaches for learning emphysema subtypes on CT are limited to texture features, which are sub-optimal due to the lack of spatial information.

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Longitudinal studies have shown that early life exposure to dichlorodiphenyl dichloroethene (DDE) can lead to growth reduction during childhood and adolescence. In addition, DDE exposure has been linked to respiratory tract infections and an increased risk of asthma in children. Our aim was to understand the relationships between DDE exposure and pulmonary function in children, and, particularly, whether associations are mediated by the height of the children.

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Cardiac computed tomography (CT) scans include approximately 2/3 of the lung and can be obtained with low radiation exposure. Large cohorts of population-based research studies reported high correlations of emphysema quantification between full-lung (FL) and cardiac CT scans, using thresholding-based measurements. This work extends a hidden Markov measure field (HMMF) model-based segmentation method for automated emphysema quantification on cardiac CT scans.

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Background. Classification of pulmonary disease into obstructive, restrictive, and mixed patterns is based on 2005 ATS/ERS guidelines and modified GOLD criteria by Mannino et al. (2003), but these guidelines are of limited use for simple spirometry in situations involving mass casualties.

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