Searched for: person:kwons04
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Partial-linear single-index Cox regression models with multiple time-dependent covariates
Lee, Myeonggyun; Troxel, Andrea B; Kwon, Sophia; Crowley, George; Schwartz, Theresa; Zeig-Owens, Rachel; Prezant, David J; Nolan, Anna; Liu, Mengling
BACKGROUND:In cohort studies with time-to-event outcomes, covariates of interest often have values that change over time. The classical Cox regression model can handle time-dependent covariates but assumes linear effects on the log hazard function, which can be limiting in practice. Furthermore, when multiple correlated covariates are studied, it is of great interest to model their joint effects by allowing a flexible functional form and to delineate their relative contributions to survival risk. METHODS:Motivated by the World Trade Center (WTC)-exposed Fire Department of New York cohort study, we proposed a partial-linear single-index Cox (PLSI-Cox) model to investigate the effects of repeatedly measured metabolic syndrome indicators on the risk of developing WTC lung injury associated with particulate matter exposure. The PLSI-Cox model reduces the dimensionality of covariates while providing interpretable estimates of their effects. The model's flexible link function accommodates nonlinear effects on the log hazard function. We developed an iterative estimation algorithm using spline techniques to model the nonparametric single-index component for potential nonlinear effects, followed by maximum partial likelihood estimation of the parameters. RESULTS:Extensive simulations showed that the proposed PLSI-Cox model outperformed the classical time-dependent Cox regression model when the true relationship was nonlinear. When the relationship was linear, both the PLSI-Cox model and classical time-dependent Cox regression model performed similarly. In the data application, we found a possible nonlinear joint effect of metabolic syndrome indicators on survival risk. Among the different indicators, BMI had the largest positive effect on the risk of developing lung injury, followed by triglycerides. CONCLUSION/CONCLUSIONS:The PLSI-Cox models allow for the evaluation of nonlinear effects of covariates and offer insights into their relative importance and direction. These methods provide a powerful set of tools for analyzing data with multiple time-dependent covariates and survival outcomes, potentially offering valuable insights for both current and future studies.
PMCID:11661057
PMID: 39707281
ISSN: 1471-2288
CID: 5765032
Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BAD-BURN) in World Trade Center exposed firefighters: a case-control observational study protocol
Javed, Urooj; Podury, Sanjiti; Kwon, Sophia; Liu, Mengling; Kim, Daniel H; Fallahzadeh, Aida; Li, Yiwei; Khan, Abraham R; Francois, Fritz; Schwartz, Theresa; Zeig-Owens, Rachel; Grunig, Gabriele; Veerappan, Arul; Zhou, Joanna; Crowley, George; Prezant, David J; Nolan, Anna
BACKGROUND:Particulate matter exposure (PM) is a cause of aerodigestive disease globally. The destruction of the World Trade Center (WTC) exposed first responders and inhabitants of New York City to WTC-PM and caused obstructive airways disease (OAD), gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE). GERD not only diminishes health-related quality of life but also gives rise to complications that extend beyond the scope of BE. GERD can incite or exacerbate allergies, sinusitis, bronchitis, and asthma. Disease features of the aerodigestive axis can overlap, often necessitating more invasive diagnostic testing and treatment modalities. This presents a need to develop novel non-invasive biomarkers of GERD, BE, airway hyperreactivity (AHR), treatment efficacy, and severity of symptoms. METHODS:Our observational case-cohort study will leverage the longitudinally phenotyped Fire Department of New York (FDNY)-WTC exposed cohort to identify Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BAD-BURN). Our study population consists of n = 4,192 individuals from which we have randomly selected a sub-cohort control group (n = 837). We will then recruit subgroups of i. AHR only ii. GERD only iii. BE iv. GERD/BE and AHR overlap or v. No GERD or AHR, from the sub-cohort control group. We will then phenotype and examine non-invasive biomarkers of these subgroups to identify under-diagnosis and/or treatment efficacy. The findings may further contribute to the development of future biologically plausible therapies, ultimately enhance patient care and quality of life. DISCUSSION/CONCLUSIONS:Although many studies have suggested interdependence between airway and digestive diseases, the causative factors and specific mechanisms remain unclear. The detection of the disease is further complicated by the invasiveness of conventional GERD diagnosis procedures and the limited availability of disease-specific biomarkers. The management of reflux is important, as it directly increases risk of cancer and negatively impacts quality of life. Therefore, it is vital to develop novel noninvasive disease markers that can effectively phenotype, facilitate early diagnosis of premalignant disease and identify potential therapeutic targets to improve patient care. TRIAL REGISTRATION/BACKGROUND:Name of Primary Registry: "Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BADBURN)". Trial Identifying Number: NCT05216133 . Date of Registration: January 31, 2022.
PMID: 39123126
ISSN: 1471-230x
CID: 5678522
Gastroesophageal Disease and Environmental Exposure: A Systematic Review [PrePrint]
Kim, Daniel; Podury, Sanjiti; Zadeh, Aida; Kwon, Sophia; Grunig, Gabriele; Liu, Mengling; Nolan, Anna
Environmental exposure-associated disease is an active area of study, especially in the context of increasing global air pollution and use of inhalants. Our group is dedicated to the study of exposure-related inflammation and downstream health effects. While many studies have focused on the impact of inhalants on respiratory sequelae, there is growing evidence of the involvement of other systems including autoimmune, endocrine, and gastrointestinal.
This systematic review aims to provide a recent update that will underscore the associations between inhalation exposures and upper gastrointestinal disease in the contexts of our evolving environmental exposures. Keywords focused on inhalational exposures and gastrointestinal disease. Primary search identified n = 764 studies, of which n = 64 met eligibility criteria. In particular, there was support for existing evidence that PM increases the risk of upper gastrointestinal diseases. Smoking was also confirmed to be major risk factor. Interestingly, studies in this review have also identified waterpipe use as a significant risk factor for gastroesophageal reflux and gastric cancer.
Our systematic review identified inhalational exposures as risk factors for aerodigestive disease, further supporting the association between environmental exposure and digestive disease. However, due to limitations on our review’s scope, further studies must be done to better understand this interaction.
ORIGINAL:0017308
ISSN: 2693-5015
CID: 5678312
Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BAD-BURN): a Case-Control Observational Study Protocol
Javed, Urooj; Podury, Sanjiti; Kwon, Sophia; Liu, Mengling; Kim, Daniel; Zadeh, Aida Fallah; Li, Yiwei; Khan, Abraham; Francois, Fritz; Schwartz, Theresa; Zeig-Owens, Rachel; Grunig, Gabrielle; Veerappan, Arul; Zhou, Joanna; Crowley, George; Prezant, David; Nolan, Anna
BACKGROUND:Particulate matter exposure (PM) is a cause of aerodigestive disease globally. The destruction of the World Trade Center (WTC) exposed first responders and inhabitants of New York City to WTC-PM and caused obstructive airways disease (OAD), gastroesophageal reflux disease (GERD) and Barrett's Esophagus (BE). GERD not only diminishes health-related quality of life but also gives rise to complications that extend beyond the scope of BE. GERD can incite or exacerbate allergies, sinusitis, bronchitis, and asthma. Disease features of the aerodigestive axis can overlap, often necessitating more invasive diagnostic testing and treatment modalities. This presents a need to develop novel non-invasive biomarkers of GERD, BE, airway hyperreactivity (AHR), treatment efficacy, and severity of symptoms. METHODS:No GERD or AHR, from the sub-cohort control group. We will then phenotype and examine non-invasive biomarkers of these subgroups to identify under-diagnosis and/or treatment efficacy. The findings may further contribute to the development of future biologically plausible therapies, ultimately enhance patient care and quality of life. DISCUSSION/CONCLUSIONS:Although many studies have suggested interdependence between airway and digestive diseases, the causative factors and specific mechanisms remain unclear. The detection of the disease is further complicated by the invasiveness of conventional GERD diagnosis procedures and the limited availability of disease-specific biomarkers. The management of reflux is important, as it directly increases risk of cancer and negatively impacts quality of life. Therefore, it is vital to develop novel noninvasive disease markers that can effectively phenotype, facilitate early diagnosis of premalignant disease and identify potential therapeutic targets to improve patient care. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov Identifier: NCT05216133; January 18, 2022.
PMCID:11118699
PMID: 38798396
CID: 5651772
Effects of E-cigarette Whole Body Aerosol Exposure on Lung Inflammation to an Acute Streptococcus Pneumoniae Challenge in Mice
Grunig, G.; Kothandaraman, C.; Ye, C.; Voynov, D.; Durmus, N.; Goriainova, V.; Raja, A.; Chalupa, D.; Weiser, J.; Kwon, S.; Nolan, A.; Elder, A.C.P.; Zelikoff, J.
ORIGINAL:0017190
ISSN: 2325-6621
CID: 5651812
Investigation of the Pulmonary and Inflammatory Profile in a Murine Model of COVID-19
Kwon, S.; Veerappan, A.; Podury, S.; Grunig, G.; Nolan, A.
ORIGINAL:0017188
ISSN: 2325-6621
CID: 5651792
Severity of COVID-19 Is Associated With Air Pollution: A Single Center Machine Learning Approach to Understand Risk
Kwon, S.; Zhao, Z.; Vora, K.; Crowley, G.; Podury, S.; Grunig, G.; Nolan, A.
ORIGINAL:0017189
ISSN: 2325-6621
CID: 5651802
Machine Learning Optimization: Defining Exposome-Metabolome Associated Aerodigestive Disease
Crowley, G.; Kwon, S.; Rushing, B.; Grunig, G.; Podury, S.; McRitchie, S.; Sumner, S.; Liu, M.; Prezant, D.J.; Nolan, A.
ORIGINAL:0017193
ISSN: 2325-6621
CID: 5651842
Aerodigestive Disease Risk Factors in Particulate Matter Exposed Firefighters
Ramprasad, M.; Phillips, O.; Lam, T.; Podury, S.; Kwon, S.; Crowley, G.; Schwartz, T.; Zeig-Owens, R.; Prezant, D.J.; Nolan, A.
ORIGINAL:0017192
ISSN: 2325-6621
CID: 5651832
Heme-oxygenase-1 Is Attenuated in a High Fat Diet Obese Mouse Model of Particulate Matter Exposure
Podury, S.; Javed, U.; Veerappan, A.; Kwon, S.; Ramprasad, M.; Phillips, O.; Lam, T.; Grunig, G.; Nolan, A.
ORIGINAL:0017194
ISSN: 2325-6621
CID: 5651852