Dynamic Metabolic Risk Profiling of World Trade Center Lung Disease: A Longitudinal Cohort Study

Association between World Trade Center disaster exposures and body mass index in community members enrolled at World Trade Center Environmental Health Center

Studies suggest that environmental disasters have a big impact on population health conditions including metabolic risk factors, such as obesity and hypertension. The World Trade Center (WTC) destruction from the 9/11 terrorist attack resulted in environmental exposures to community members (Survivors) with potential for metabolic effects. We now examine the impact of WTC exposure on Body Mass Index (BMI) using the data from 7136 adult participants enrolled in the WTC Environmental Health Center (EHC) from August 1, 2005, to December 31, 2022. We characterized WTC-related exposures by multiple approaches including acute dust-cloud exposure, occupational or residential exposures, and latent exposure patterns identified by synthesizing multiplex exposure questions using latent class analysis. Employing multivariable linear and quantile regressions for continuous BMI and ordered logistic regression for BMI categories, we found significant associations of BMI with WTC exposure categories or latent exposure patterns. For example, using exposure categories, compared to the group of local residents, local workers exhibited an average BMI increase of 1.71 kg/m2 with 95% confidence intervals (CI) of (1.33, 2.09), the rescue/recovery group had an increase of 3.13 kg/m2 (95% CI: 2.18, 4.08), the clean-up worker group had an increase of 0.75 kg/m2 (95% CI: 0.09, 1.40), and the other mixer group had an increase of 1.01 kg/m2 (95% CI: 0.43, 1.58). Furthermore, quantile regression analysis demonstrated that WTC exposures adversely affected the entire distribution of BMI in the WTC EHC Survivors, not merely the average. Our analysis also extended to blood pressure and hypertension, demonstrating statistically significant associations with WTC exposures. These outcomes highlight the intricate connection between WTC exposures and metabolic risk factors including BMI and blood pressure in the WTC Survivor population.

Partial-linear single-index Cox regression models with multiple time-dependent covariates

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

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.

Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BAD-BURN) in World Trade Center exposed firefighters: a case-control observational study protocol

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

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

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.

Biomarkers of Airway Disease, Barrett's and Underdiagnosed Reflux Noninvasively (BAD-BURN): a Case-Control Observational Study Protocol

BACKGROUND

Particulate matter exposure (PM) is a cause of aerodigestive disease globally. The destruction of the World Trade Center (WTC) exposed fifirst responders and inhabitants of New York City to WTC-PM and caused obstructive airways disease (OAD), gastroesophageal Refux 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 Refux 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

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 Refux 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

ClinicalTrials.gov Identifier: NCT05216133; January 18, 2022.

Perceptions of Preventable Cancer Burden Among US-Based Firefighters: A Mixed Methods Cross-Sectional Study

OBJECTIVE

Characterize experiences with cancer and perceptions of the preventable cancer burden attributable to diet among firefighters.

DESIGN

A cross-sectional survey was distributed to assess cancer history and perceptions of cancer.

SETTING

US.

PARTICIPANTS

US-based firefighters.

MAIN OUTCOME MEASURE(S)

History of cancer, perceptions of cancer, and perceptions of diet as a means to prevent cancer.

ANALYSIS

Descriptive statistics and use of the Behaviour Change Technique Taxonomy v1 (BCTTv1) to evaluate qualitative responses.

RESULTS

A total of 471 firefighters participated. Nearly half (48.4%) voiced they strongly agreed that they were at risk for cancer, whereas 44.6% agreed that changing diet could decrease cancer risk. The most common BCTTv1 codes focused on types of education, including "Instruction on how to perform the behavior" (45.1%, n = 189), followed by those centered on behavior execution (eg, "Action planning" [24.8%, n = 104]). Qualitatively, many were concerned about misinformation.

CONCLUSIONS AND IMPLICATIONS

Firefighters acknowledge the role of diet in cancer risk and have a desire for knowledge and behavioral support (eg, goal setting) that includes an emphasis on evidence and tackling misinformation. This information should serve as the basis of future interventions that target diet.

The Impact of Metabolic Syndrome Risk Factors on Lung Function Impairment: Cross-Sectional Study

BACKGROUND

Metabolic syndrome (MetS) is a constellation of risk factors increasingly present in the world's population. People with this syndrome are at an increased risk of cardiovascular disease and type 2 diabetes mellitus. Moreover, evidence has shown that it affects different organs. MetS and its risk factors are independently associated with impaired lung function, which can be quantified through spirometric variables.

OBJECTIVE

This study aims to determine whether a high number of MetS criteria is associated with increased lung function decline.

METHODS

We conducted a descriptive cross-sectional study with a random sample of 1980 workers. Workers with acute respiratory pathology (eg, influenza), chronic respiratory pathology (eg, chronic bronchitis), or exposure to substances harmful to the lungs (eg, organic and inorganic dust) were not included. MetS was established based on harmonized criteria, and lung function was assessed according to spirometric variables. On the basis of these, classification into restrictive lung disease (RLD), obstructive lung disease, and mixed lung disease (MLD) was performed. In addition, the association between MetS and lung function was established based on analysis of covariance, linear trend analysis, and multiple linear regression.

RESULTS

MetS was associated with worse lung function according to all the spirometric parameters analyzed (percentage of predicted forced expiratory volume in 1 second: mean 83, SD 13.8 vs mean 89.2, SD 12.8; P<.001 and percentage of predicted forced vital capacity: mean 85.9, SD 11.6 vs mean 92, SD 11.3; P<.001). Moreover, those diagnosed with MetS had a higher prevalence of lung dysfunction (41% vs 21.9%; P<.001), RLD (23.4% vs 11.2%; P<.001), and MLD (7.3% vs 2.2%; P<.001). Furthermore, an increasing number of MetS criteria was associated with a greater impairment of pulmonary mechanics (P<.001). Similarly, with an increasing number of MetS criteria, there was a significant linear trend (P<.001) in the growth of the prevalence ratio of RLD (0 criteria: 1, 1: 1.46, 2: 1.52, 3: 2.53, 4: 2.97, and 5: 5.34) and MLD (0 criteria: 1, 1: 2.68, 2: 6.18, 3: 9.69, and 4: 11.37). Regression analysis showed that the alteration of all MetS risk factors, adjusted for various explanatory variables, was significantly associated with a worsening of spirometric parameters, except for forced expiratory volume in 1 second/forced vital capacity.

CONCLUSIONS

The findings have shown that an increase in cardiometabolic risk factors is associated with a more significant worsening of spirometric variables and a higher prevalence of RLD and MLD. As spirometry could be a crucial tool for monitoring patients at risk of developing chronic pathologies, we conclude that this inexpensive and easily accessible test could help detect changes in lung function in patients with cardiometabolic disorders. This highlights the need to consider the importance of cardiometabolic health in lung function when formulating public health policies.

Metabolomics of Respiratory Diseases

Metabolomics is an expanding field of systems biology that is gaining significant attention in respiratory research. As a unique approach to understanding and diagnosing diseases, metabolomics provides a snapshot of all metabolites present in biological samples such as exhaled breath condensate, bronchoalveolar lavage, plasma, serum, urine, and other specimens that may be obtained from patients with respiratory diseases. In this article, we review the rapidly expanding field of metabolomics in its application to respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), pneumonia, and acute lung injury, along with its more severe form, adult respiratory disease syndrome. We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized occupational and environmental materials. With the latest advances in our understanding of the microbiome, we discuss microbiome-derived metabolites that arise from the gut and lung in asthma and COPD that have mechanistic implications for these diseases. Recent literature has suggested that metabolomics analysis using nuclear magnetic resonance (NMR) and mass spectrometry (MS) approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe diseases which may be fatal for many patients each year.

Molecular Clustering Analysis of Blood Biomarkers in World Trade Center Exposed Community Members with Persistent Lower Respiratory Symptoms

The destruction of the World Trade Center (WTC) on September 11, 2001 (9/11) released large amounts of toxic dusts and fumes into the air that exposed many community members who lived and/or worked in the local area. Many community members, defined as WTC survivors by the federal government, developed lower respiratory symptoms (LRS). We previously reported the persistence of these symptoms in patients with normal spirometry despite treatment with inhaled corticosteroids and/or long-acting bronchodilators. This report expands upon our study of this group with the goal to identify molecular markers associated with exposure and heterogeneity in WTC survivors with LRS using a selected plasma biomarker approach. Samples from WTC survivors with LRS (n = 73, WTCS) and samples from healthy control participants of the NYU Bellevue Asthma Registry (NYUBAR, n = 55) were compared. WTCS provided information regarding WTC dust exposure intensity. Hierarchical clustering of the linear biomarker data identified two clusters within WTCS and two clusters within NYUBAR controls. Comparison of the WTCS clusters showed that one cluster had significantly increased levels of circulating matrix metalloproteinases (MMP1, 2, 3, 8, 12, 13), soluble inflammatory receptors (receptor for advanced glycation end-products-RAGE, Interleukin-1 receptor antagonist (IL-1RA), suppression of tumorigenicity (ST)2, triggering receptor expressed on myeloid cells (TREM)1, IL-6Ra, tumor necrosis factor (TNF)RI, TNFRII), and chemokines (IL-8, CC chemokine ligand- CCL17). Furthermore, this WTCS cluster was associated with WTC exposure variables, ash at work, and the participant category workers; but not with the exposure variable WTC dust cloud at 9/11. A comparison of WTC exposure categorial variables identified that chemokines (CCL17, CCL11), circulating receptors (RAGE, TREM1), MMPs (MMP3, MMP12), and vascular markers (Angiogenin, vascular cell adhesion molecule-VCAM1) significantly increased in the more exposed groups. Circulating biomarkers of remodeling and inflammation identified clusters within WTCS and were associated with WTC exposure.

Twenty-Year Reflection on the Impact of World Trade Center Exposure on Pulmonary Outcomes in Fire Department of the City of New York (FDNY) Rescue and Recovery Workers

After the terrorist attacks on September 11, 2001 (9/11), many rescue/recovery workers developed respiratory symptoms and pulmonary diseases due to their extensive World Trade Center (WTC) dust cloud exposure. Nearly all Fire Department of the City of New York (FDNY) workers were present within 48 h of 9/11 and for the next several months. Since the FDNY had a well-established occupational health service for its firefighters and Emergency Medical Services workers prior to 9/11, the FDNY was able to immediately start a rigorous monitoring and treatment program for its WTC-exposed workers. As a result, respiratory symptoms and diseases were identified soon after 9/11. This focused review summarizes the WTC-related respiratory diseases that developed in the FDNY cohort after 9/11, including WTC cough syndrome, obstructive airways disease, accelerated lung function decline, airway hyperreactivity, sarcoidosis, and obstructive sleep apnea. Additionally, an extensive array of biomarkers has been identified as associated with WTC-related respiratory disease. Future research efforts will not only focus on further phenotyping/treating WTC-related respiratory disease but also on additional diseases associated with WTC exposure, especially those that take decades to develop, such as cardiovascular disease, cancer, and interstitial lung disease.