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

Biomarkers of Airway Disease, Barrett’s and Underdiagnosed Reflux Noninvasively (BAD-BURN): a Case-Control Observational Study Protocol | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Study protocol Biomarkers of Airway Disease, Barrett’s and Underdiagnosed Reflux Noninvasively (BAD-BURN): a Case-Control Observational Study Protocol Urooj Javed, Sanjiti Podury, Sophia Kwon, Mengling Liu, Daniel Kim, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4355584/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Aug, 2024 Read the published version in BMC Gastroenterology → Version 1 posted 4 You are reading this latest preprint version Abstract 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 B iomarkers of A irway D isease , B arrett’s and U nderdiagnosed R eflux N oninvasively (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: ClinicalTrials.gov Identifier: NCT05216133; January 18, 2022. Air Pollutants Airway hyperreactivity Ambient Particulate Matter Barrett's Esophagus Gastro-Esophageal Reflux Disease Particulate Aerodigestive Figures Figure 1 Figure 2 BACKGROUND Particulate matter (PM) exposure is a risk factor for aerodigestive disease and mortality. 1 – 3 On September 11, 2001 (9/11), first-responders and inhabitants of New York City were exposed to World Trade Center (WTC)-PM. 4 – 35 Many subsequently developed aerodigestive diseases including obstructive airways disease (OAD), gastroesophageal reflux disease (GERD) and Barrett’s Esophagus (BE). 23 , 34 , 36 – 42 By 2005, approximately 44% of WTC rescue and recovery workers had developed GERD, which is 8.2-fold higher than the pre-9/11 prevalence, and more than double the general US population. 43 – 46 After WTC-PM exposure, GERD occurred more often in asthmatics. 42 Comorbid aerodigestive disease affected 51.4% of firefighters. 47 GERD and BE are risk factors for esophageal adenocarcinomas (EAC). 48 Patients with BE face at least 30-fold higher risk of developing EAC than the general population. 49 , 50 Complications of GERD extend beyond malignancy and can adversely affect quality of life (QoL), impair productivity, and lifespan. 46 , 51 – 53 GERD can incite or exacerbate co-morbidities such as allergies, sinusitis, chronic bronchitis, and asthma. 54 There is a 59.2% prevalence of GERD symptoms in patients with asthma compared to 38.1% in controls. 55 GERD treatment in WTC responders with proton pump inhibitors (PPIs) have been found to increase risk of severe cognitive impairment. 56 Cognitive decline with PPI use has also been reported in the general population. 57 Despite numerous studies suggesting potential interdependence between airway and digestive diseases, the underlying causative factors and mechanisms remain unclear. 55 Biomarkers are often key to identifying causative pathways and mechanistic targets. While some studies have investigated serum, salivary, and microbial biomarkers of GERD, they are often not focused on the contribution of respiratory disease. 58 – 60 The availability of clinical longitudinal phenotyping makes the WTC-PM exposed Fire Department of New York (FDNY) first responders cohort ideal for biomarker discovery. 10,22,28–31,61−65 Notably, we have successfully identified biomarkers associated with GERD and BE in a pilot population with respiratory disease, facilitating the identification of biologically relevant immune pathways. 3 The diagnosis of GERD itself is a complex process that relies on subjective clinical symptoms and often necessitate objective but invasive testing such as endoscopy and 24-hour pH monitoring. 66 Those with endoscopic evidence of reflux may be entirely asymptomatic, potentially leading to under-diagnosis of patients at risk of BE and EAC. 67 , 68 Even with the most invasive procedures, the diagnosis of GERD can be elusive and plagued by poor sensitivity. 69 In light of this, we propose to explore noninvasive biomarkers that could identify a population of aerodigestive disease, enabling better phenotyping of FDNY-WTC cohort with aerodigestive disease. In addition to their diagnostic utility, noninvasive biomarkers may direct future research into mechanisms and their downstream effects. GERD/BE biomarkers are also important to identify in the clinically silent presentations. 69 Additionally, we will identify novel non-invasive biomarkers of aerodigestive disease through a multi-OMIC approach. We will profile not only the metabolome and microbiome, but also exhaled, secreted, and blood biomarkers of aerodigestive disease, Fig. 1 . 70 To address a critical gap in the current literature, we will 1. Quantify noninvasive measures of aerodigestive disease (salivary pepsin, serum biomarkers/metabolome, fractional exhaled nitric oxide (FeNO), exhaled breath condensate (EBC), microbiome, cognitive measures and aerodigestive QoL/disease severity measures to phenotype and assess treatment efficacy. 2. Develop and optimize a noninvasive biomarker model of aerodigestive disease and also 3. determine the effect of aerodigestive disease on QoL, cognition and symptom phenotype. METHODS/DESIGN Study Design and Participants. The FDNY WTC-health program (WTC-HP) electronic medical record (EMR) will be used to obtain clinical variables such as age, gender, years of FDNY service, WTC site exposure level, and lung function measures, as previously described. 22 , 27 , 62 – 65 , 71 Our observational study is NYU IRB Approved # 21–00679 and available at clinicaltrials.gov #NCT05216133. Study Definitions and Inclusion/Exclusion Criteria can be found in Table 1. Study Population : Source Cohort. All participants in the WTC-HP (n = 14,976) were screened, Fig. 2 . Inclusion Criteria : i. Actively consented and enrolled member of the WTC-HP. ii. Pre-9/11 spirometry with Forced Expiratory Volume in 1 second (FEV 1 ) ≥ Lower Limit of Normal (LLN) iii. Male Firefighter status on 9/11 with exposure at the WTC-site and entry into WTC-HP before the site closure on 7/24/2002. Exclusion Criteria : i. lung disease prior to 9/11 as defined by positive methacholine or bronchodilator test, or FEV 1 < LLN. ii. Not part of initial cohort in data extraction from August 1, 2017. 72 After all inclusion/exclusion criteria applied, the baseline cohort consists of n = 4,192. Sub-cohort Development. A representative cohort of 20% was randomly selected (n = 837; SPSS v. 28) from the above baseline cohort, Fig. 2 . Recruited Cohort will be developed to assess for noninvasive biomarkers. We will recruit a subset N = 40/group ( i. AHR only ii. GERD only iii. BE iv. GERD/BE and AHR overlap or v. No GERD nor AHR) from the sub-cohort, Fig. 2 . Recruitment strategies will include: i. Direct mailings; ii. Email (potential participants will be sent the same IRB-approved recruitment message to their personal emails using end-to-end encryption; iii. Study website will include recruitment messages providing general information on the study and answers to frequently-asked questions. No direct communications will be made with participants through the website, and no PHI will be used or available within the study website; iv. Telephone contact. A description of the study will be provided to potential participants and, upon their expression of interest, the investigator will perform an eligibility screening. In addition to meeting the inclusion criteria as outlined above, participants should: i. have available serum from their first post 9/11 WTC-HP ii. not currently be receiving treatment for malignancy iii. have no limitations to a minimal risk blood draw iv. be willing and able to sign consent; and v. be able to attend a single-visit. Case Status. WTC-AHR will be defined as having a positive methacholine (PC 200 < 16), or a positive bronchodilator response (by ATS/ERS guidelines with improvement of FEV 1 by 12% and at least 200mL) at least once post-9/11 73,74 and/or EMR diagnosis. GERD will be defined as: biopsy-proven erosive esophagitis LA grade C or D; stricture or Barrett’s esophagus on endoscopy; and/or esophageal acid exposure time > 6% on a pH or pH impedance study. GERD will also be defined on EMR diagnosis and/or PPIs, H 2 blockers, antacid, or surface agent use. 75 BE , as a subset of GERD, will have any of the following additional inclusion criteria: biopsy-proven columnar epithelium lining ≥ 1cm of the distal esophagus with intestinal metaplasia characterized with goblet cells on histology; diagnosis on EMR, Table 2-3 . 75 The recruited participants will be consented prior to any research activity and measurement visit via REDCap software or in person. Measurement Visit. Participant demographic information, medical history and medication history will be obtained. A physician will perform the physical examination, and verify that inclusion/exclusion criteria are met. Enrolled participants will undergo the following assessments. Blood Sampling. After at least an 8 hour fast, serum and plasma will be obtained, aliquoted and banked. Each stored specimen will be assigned a unique code to ensure proper identification and linkage to the respective participant. Aliquots from the fresh samples will be assayed for complete blood count (with differential) and chemistry panel. These data are already available for the banked samples. For all samples, lipid profile, metabolomics, and protein biomarker profiling will be performed. 10 , 28 – 30 , 76 , 77 Salivary Pepsin Assessment. 30mL sterile plastic tubes with 0.5 ml of 0.01M citric acid, adjusted to a pH of 2.5 (RD Biomed Ltd., Hull, UK), will be used by the participants to collect saliva in the AM (prior to brushing teeth, drinking or eating), 1h after finishing lunch, and 1h after finishing dinner. 78 , 79 Participants will be instructed to cough a few times prior to spitting into the tube to clear saliva from the back of the throat and then spit into the tube. The collected samples will be stored at 4°C and analyzed within 2 days. Salivary Pepsin will be analyzed using Peptest (RD Biomed Ltd., Hull, UK) as previously described. 79 Briefly, plastic tubes will be centrifuged at 4,000 rpm for 5 minutes, and 80µL of supernatant will be added to 240µL of migration butter solution for 10 seconds. 80µL of the mixture will be added to the well of the Peptest, which contains two unique human monoclonal antibodies that detect and capture pepsin protein (specific to pepsin-3), with a lower limit of detection of 16 ng/mL and an upper limit of 500 ng/mL. A salivary pepsin level of ≥ 16 ng/mL will be considered positive. The sample will be processed in a Pepcube reader to quantify the pepsin concentration. 78 Spirometry will be assessed using a KoKo PFT spirometer (nSpire Health Inc), and lung function assessment will be considered acceptable as per the ATS/ERS guidelines. 80 We will select the largest acceptable measures for electronic archiving. Each participant’s predicted percentage (%) will be calculated by NHANES III equations based on their age at examination, height, sex, and race. 80 , 81 FeNO will be quantified using NIOX VERO® (Aerocrine). 82 , 83 Participants will be instructed to inhale to their total lung capacity via mouthpiece for 2–3 seconds. Then, they will exhale at a flow rate of 0.05L/second. The device will provide results in parts per billion (ppb). Exhaled breath condensate (EBC ) will be collected using RTubes (Respiratory Research, Inc., USA). 84 Approximately 1-2mL of EBC sample will be obtained after 10 min of quiet normal breathing. 85 PH measurement. EBC pH assay is extremely simple to perform, inexpensive, and robust, and can be easily processed on the day of collection. 86 EBC will be de-aerated of CO 2 by bubbling free argon gas (350ml/min) under a micro-pH reader (Orion PerpHecT micro-pH electrode) and stabilized pH will be recorded after approximately 3–5 minutes. 87 Aliquots are then stored at -80⁰C and thawed only once prior to histamine and biomarker assessment. Naso/oropharyngeal microbiome. Collection. Trained study team members will collect naso/oropharyngeal samples using commercially available kits (OMR-110 by DNA Genotek, Canada). Each naris will be swabbed in a circular fashion 10 times. The oropharyngeal sample will be collected by swabbing in the back of the throat in 10 circular motion to ensure sufficient swab collection. Each absorbent swab will be placed into a vial containing 1 mL of stabilizing liquid using aseptic technique. The sample will be treated with lyophilized Proteinase K, and incubated in the original vial at 50⁰C for 1 hour in a water bath prior to aliquoting for long-term storage at -80⁰C. Quality of Life, Aerodigestive Disease and End-Organ Effect Questionnaires. Gastrointestinal impact will be assessed using with the Patient Assessment of Upper Gastrointestinal Disorders – Quality of Life (PAGI-QoL) and the Patient Assessment of Upper Gastrointestinal Disorders Symptom Severity Index (PAGI-SYM). Both questionnaires use a 6-point Likert scale (MAPI Research Trust). 88 – 91 Respiratory and QoL assessment will utilize the Health-Related Quality of Life measures (HRQL) 92 , St. George’s Respiratory Questionnaire ( SGRQ ), and the Short-form-36 ( SF-36 ). HRQL assesses an individual's perceived physical and mental health. The SGRQ is a standardized, self-administered airways disease-specific questionnaire divided into three subscales- symptoms, activity, and impact. 93 SF-36 will capture supplemental information about their mental health, general health perception, emotional, and social role functioning. 94 Cognition will be assessed using the Montreal Cognitive Assessment ( MoCA; version 8.1) and the Mini-Mental State Examination (MMSE) . MMSE is a cognitive test used to evaluate early dementia. 95 , 96 Combining MoCA and MMSE can improve diagnostic utility. 97 The MoCA will be administered by a trained/certified investigator. Members of our research team have completed MoCA training and certification through a validated MoCA cognition portal 98 ( https://mocacognition.com/ ). Similar to the MoCA, the MMSE assesses orientation, memory, visuospatial and language domains. Additionally, the MMSE evaluates comprehension, reading and writing. 99 The PI will thoroughly review all scores. Power Analysis . A sample size of 40 cases for each group of GERD, AHR, AHR/GERD overlap, BE, and non-GERD/non-AHR Controls (all will be subsets of AIM 1 N = 898 randomly selected cohort) achieves 80% power to detect difference as small as 0.78 SD with two-sample t-test at 0.01 significance level to account for multiple comparisons. This will allow us to achieve 80% power and significance of 0.05, based on prior studies with salivary pepsin test (personal communication with Dr. Peter Dettmar of Peptest), Fig. 2 . Statistical Analysis SPSS 28 (IBM) will facilitate database management and statistics. Continuous variables expressed as mean, standard deviation (SD) if normally distributed, and as median, inter-quartile range (IQR) if skewed. Two-sample t-test and ANOVA will compare continuous data. Count and proportions will summarize categorical data and Pearson-χ 2 will compare categorical data. Multivariate binary logistic regression will estimate biomarker-disease relationship for case status as a binary outcome while adjusting for confounding. Cox proportional hazards model will evaluate the effects of biomarkers, smoking, and exposure on the hazard of developing WTC-GERD or BE over time. The maximum potential effectiveness of a biomarker will be calculated by Youden Index. 100 Goodness of fit, using the Hosmer-Lemeshow test. Survival curves compared by Log-rank test. Pearson 𝜒 2 -test will compare SABA and LABA usage between GERD, AHR, AHR/GERD overlap, BE, and non-GERD or AHR controls. Significance will be assessed by p < 0.05 for all statistical tests. Graphs will be created using Prism (v.10, GraphPad Software). Missing data Variables with missing values in a small proportion of participants will be imputed using multiple imputation methods. To assess the missing at random assumption, we will evaluate the comparability between samples with missing data and those without. Sensitivity analysis will be performed by comparing the results obtained from the complete data analysis to the results obtained from multiple imputation. Model Building. We have previously identified key biomarkers using a machine learning approach. 10 , 28 – 30 We have further refined this analysis pipeline and will utilize this methodology to identify AHR, GERD, AHR/GERD overlap, and BE biomarkers. Specifically, we will utilize random forests (RF) of the filtered, normalized biomarkers. Models assessed via a modified hamming distance between variable importance rankings of models with identical hyper-parameters. A refined profile of the top 5% of important biomarkers by MDA will be included in a gradient-boosted tree model (xgboost package, R-Project) to build a classifier of AHR, GERD, AHR/GERD overlap, and BE. A random hyperparameter space search determined a final model that maximized AUC ROC . We will also use linear mixed-effects models will be used to assess the temporal trend of biomarkers with time adjusting for confounders. The longitudinal biomarkers processes will be associated to risk of developing WTC-GERD/BE using the joint modeling technique. 101 The joint-modeling approach has become the primary method for analysis of longitudinal biomarker process and time-to-event outcome, and multiple R packages are available to implement the models. We will also consider a single index longitudinal model which enables us to reduce the dimensionality of multiple biomarkers and to evaluate joint effects of multiple biomarkers together to identify key risk factors. The single-index model incorporates longitudinal data to calculate hazard of each parameter as well as personalized dynamic risk for prognostication. Specifically, this will allow us to use a patient’s data from a single clinical exam to identify risk of GERD, AHR, overlap, or BE. Furthermore, this will allow the identification of false negatives and undertreated cases in the entire FDNY cohort. DISCUSSION PM exposure, a significant component of ambient and occupational exposures is a risk factor for aerodigestive disease (such as GERD and AHR) and is associated with approximately 7 - million deaths annually. 1 – 3 , 11 , 102 – 104 GERD is the most prevalent gastrointestinal disorder in the US, with an estimate as high as 30%. 66 Globally, the prevalence of GERD ranges from 10–25%, with an increased risk in firefighters. 52 , 66 GERD is an independent risk factor in the development of BE which can lead to malignancy. 66 Despite the similar risks, the understanding of the underlying pathophysiological interrelatedness between the aerodigestive diseases (AHR, GERD and BE) remains limited. Furthermore, GERD diagnosis and treatment has been invasive and costly. Therefore, our work is focused on identifying non-invasive biomarkers which may help identify at risk populations who may benefit from earlier intervention, targeted therapies and a further understanding of how their AHR is impacted by co-morbid GERD. The identification of non-invasive biomarkers of GERD/BE and the overlapping aerodigestive disease is crucial. Our work will address the existing knowledge gap in aerodigestive overlap and validate biomarkers of WTC-aerodigestive disease. Biomarkers of BE may also identify individuals at risk for neoplastic disease. These findings may have broader implications for populations with GERD and PM exposure. In contrast to currently used invasive testing, noninvasive testing offers diagnostic utility with reduced risk and can direct future research into mechanisms/downstream effects. We also systematically studied biomarkers of GERD/BE and defined some of the lacunae in the non-invasive aerodigestive biomarker literature. 105 Therefore, our Case-Control Observational Study is designed to sample a broad biomarker profile, Table 3 . Microbiome of the Gut/Lung Axis. Asthma susceptibility is influenced by the gut microbiome. 106 – 111 Noninvasive collection sites that can approximate the pulmonary environment are of key interest. Studies have failed to show that the microbiomes of induced sputum were similar to the lung. 112 , 113 Noninvasively collected oropharyngeal and nasopharyngeal swabs in conjunction could approximate the lung microbiome. 114 Research has revealed that the esophageal microbiome undergoes alteration in individuals with GERD, BE, and other motility disorders. 115 , 116 Although these findings highlight the potential role of the microbiome studies in the diagnosis and therapeutic approaches for aerodigestive disease, further studies are needed and will be one of the key readouts planned in our study. EBC analysis holds great promise in addressing unmet medical needs by expanding the portfolio of noninvasive assays for the multiple coexisting pathological mechanisms underlying respiratory disorders and GERD. Compounds identified in EBC include histamine, adenosine, ammonia, hydrogen peroxide, isoprostanes, leukotrienes, nitrogen oxides (NOx), peptides, cytokines, protons and various ions. 85 Histamine plays a vital role in digestion but elevated levels can contribute to the development of GERD. 117 , 118 Salivary pepsin has been studied in several GERD biomarker studies. 105 Due to the overlap of various reflux symptoms with other GI pathologies, the diagnosis of GERD can be challenging. However, salivary pepsin test offers a simple and convenient way for detecting reflux through salivary sample collection, providing quick and non-invasive results. Compared to other diagnostic modalities, this approach is time-efficient and requires much less effort. 119 Moreover, pepsin measurements can identify pathologic reflux even in the absence of symptoms, and remain unaffected by the concurrent use of PPI. Several studies have demonstrated that pepsin detection in the sputum and/or saliva can be regarded as a sensitive, non-invasive method for the diagnosis of the proximal reflux of gastric contents, with a sensitivity ranged from 41.5–73% and high specificity of 86.2 to 98.2%. 78,79 Despite these findings little is known about pepsin in the context of aerodigestive co-morbid disease. FeNO , a biomarker of lung disease activity, will be a valuable measure in our population. FeNO is associated with airway hyperreactivity, and several studies demonstrated that FeNO is increased during obstructive exacerbations. 120 In our population with the aerodigestive overlap, FeNO levels can serve as an indicator of potential underlying AHR exacerbating symptoms of GERD. Thus, our work will also contribute to understand the role of FeNO in GERD, which remains inconclusive as only a limited number of studies have examined AHR/GERD. 121,122 The detrimental impact of even once-weekly episodes of GERD on quality of life 123 highlighted the importance of assessing aerodigestive disease quality of life and disease activity, therefore we will quantify the effects of GERD on these aspects through a validated set of questionnaires that will assess QoL, GERD specific symptoms and also cognitive involvement. Non-invasive biomarkers of GERD, BE, AHR, treatment efficacy, and severity of symptoms will also be assessed in serum. This will allow us to measure Tumor Necrosis Factor (TNF-α), C-peptide, Fractalkine and Interferon-gamma-induced Protein 10 (IP-10) in our case cohort study to validate our prior pilot study. 1 – 3 Serum samples will also be used to perform metabolomic profiling that will allow us to investigate metabolic correlates of aerodigestive disease. In addition, by validating serum biomarkers (proteins and metabolome) of GERD/BE, we seek to provide a biologically plausible target that enables early detection and facilitates therapeutic intervention in the PM exposed populations. Moreover, non-invasive phenotyping of WTC aerodigestive disease holds promise in improving the sensitivity and specificity of GERD diagnosis, enabling earlier identification of BE and facilitate the development of personalized therapy, thus to improve both the quality of life and overall health outcomes. Limitations and potential study concerns . We envision there are several limitations of our study. It is possible that no significant association exists between noninvasive biomarkers and aerodigestive diseases in the second decade after WTC exposure. The generalizability of our study could be impacted because the FDNY source cohort had no aerodigestive disease prior to 9/11 and had their serum samples banked within six months of 9/11, therefore making it less comparable to other cohorts. There may also be a subset of patients without history of GERD, but could still receive a clinical diagnosis of GERD based on questionnaires and/or elevated pepsin/biomarkers. For these patients, further follow-up with a gastroenterologist will be recommended. Additionally, we may use FeNO levels to identify the potential underlying AHR exacerbating symptoms associated with GERD. We will also account for the potential risk of loss to follow-up regarding the completion of the questionnaires and attendance of the in-person visit. Further investigation into the overlap of GERD/BE and AHR is envisioned to provide valuable insights in distinguishing disease phenotypes, demonstrating that biomarkers can predict GERD and/or BE. This work will have clinical implications for the diagnosis and treatment of WTC associated disease, as well as for the management of other patients in the WTC monitoring programs, and for the general population as intense PM exposures are occurring more frequently, for example through wild fire related PM. Our research will contribute to the development of a robust biomarker set with optimal explanatory power when applied to diverse cohorts. Abbreviations AHR Airway Hyper reactivity BADBURN Biomarkers of Airway Disease, Barrett’s and Underdiagnosed R eflux N oninvasively BMI Body Mass Index (kg/m 2 ) COPD Chronic Obstructive Pulmonary Disease DBP Diastolic Blood Pressure DSMB Data and Safety Monitoring Board EAC esophageal adenocarcinomas ECG Electrocardiogram FDNY Fire Department of New York FE NO Fractional Exhaled Nitric Oxide FEV 1 Forced Expiratory Volume in 1 second FVC Forced Vital Capacity HRQL Health-Related Quality of Life HP Health Program IRB Internal Review Board LI lung Injury LLN Lower Limit of Normal LoCalMed Low Calorie Mediterranean Diet MetSyn Metabolic Syndrome MoCA Montreal Cognitive Assessment MMSE Mini-Mental State Examination MOP Manual of Procedures MND MyNetDiary N Number NIH National Institutes of Health NYU New York University OAD Obstructive Airways Disease PAGI-QOL Patient Assessment of Upper Gastrointestinal Disorders- Quality of Life PAGI-SYM Patient Assessment of Upper Gastrointestinal Disorders- Symptoms Severity PI Principal Investigator PM Particulate Matter PWV Pulse Wave Velocity QoL Quality of Life RCT Randomized Clinical Trial SBP Systolic Blood Pressure SF-36 Short-Form 36 SGRQ St. George’s Respiratory Questionnaire SOP Standard Operating Procedure US United States WTC World Trade Center 9/11 September 11, 2001 Declarations Ethics approval and consent to participate. Participants signed informed consent at the time of enrollment allowing analysis of their information and samples for research. This study was approved by the Institutional Review Boards of Montefiore Medical Center (#07-09-320) and New York University (NYU IRB # 21-00679). Consent for publication. Not applicable Availability of data and materials. The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests. The authors declare that they have no competing interests. Funding. CDC/NIOSH U01-OH012069; U01-OH011300 and U01-OH011855; NIH/NIEHS, R01ES032808; Clinical Center of Excellence 200-2017-93426 and Data Center 200-2017-93326. Authors’ contributions. AN was the primary investigator, had full access to all of the data in the study and takes responsibility for the integrity and the accuracy of the data analysis. UJ, SK, SP, FF, ARK and AN participated in study conception and design; UJ, SP, SK, RZO, TS, DP and AN were responsible for data collection; SK and AN were responsible for data validation; UJ, SP, SK, GG, and ML participated in data analysis. All authors including ( DHK, AFZ, YL, AV, JZ, and GC ) participated in data interpretation, writing and revision of the report and approval of the final version. Acknowledgements. The authors would like to thank the FDNY first responders for their bravery and for taking part in our study, References Seo HS, Hong J, Jung J. Relationship of meteorological factors and air pollutants with medical care utilization for gastroesophageal reflux disease in urban area. World J Gastroenterol. 2020;26:6074–86. Gaffney KF. Infant exposure to environmental tobacco smoke. J Nurs Scholarsh. 2001;33:343–7. Haider SH, et al. 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Gastro-oesophageal reflux symptoms and health-related quality of life in the adult general population - the Kalixanda study. Aliment Pharm Ther. 2006;23:1725–33. Tables Tables 1 to 3 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files 02BBADBURNTABLE120240501.pdf 02BBADBURNTABLE220240501.pdf 02BBADBURNTABLE320240501.pdf Cite Share Download PDF Status: Published Journal Publication published 09 Aug, 2024 Read the published version in BMC Gastroenterology → Version 1 posted Editorial decision: Revision requested 14 May, 2024 Editor assigned by journal 08 May, 2024 Submission checks completed at journal 07 May, 2024 First submitted to journal 01 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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15:49:09","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":135365,"visible":true,"origin":"","legend":"","description":"","filename":"02BBADBURNTABLE120240501.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4355584/v1/02ed71182a0c01c46f1b3f7d.pdf"},{"id":56550036,"identity":"0d34ba8e-b45b-4d3e-b49a-ab7c0d4194c8","added_by":"auto","created_at":"2024-05-15 15:49:09","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":97802,"visible":true,"origin":"","legend":"","description":"","filename":"02BBADBURNTABLE220240501.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4355584/v1/1fb4032f75f921471eaeb96c.pdf"},{"id":56550034,"identity":"8b571993-9cf5-4fae-bbb6-e64f4c1d38ab","added_by":"auto","created_at":"2024-05-15 15:49:09","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":76375,"visible":true,"origin":"","legend":"","description":"","filename":"02BBADBURNTABLE320240501.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4355584/v1/2a9485d767d9be893313b058.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Biomarkers of Airway Disease, Barrett’s and Underdiagnosed Reflux Noninvasively (BAD-BURN): a Case-Control Observational Study Protocol","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eParticulate matter (PM) exposure is a risk factor for aerodigestive disease and mortality.\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e On September 11, 2001 (9/11), first-responders and inhabitants of New York City were exposed to World Trade Center (WTC)-PM.\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13 CR14 CR15 CR16 CR17 CR18 CR19 CR20 CR21 CR22 CR23 CR24 CR25 CR26 CR27 CR28 CR29 CR30 CR31 CR32 CR33 CR34\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e Many subsequently developed aerodigestive diseases including obstructive airways disease (OAD), gastroesophageal reflux disease (GERD) and Barrett\u0026rsquo;s Esophagus (BE).\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan additionalcitationids=\"CR37 CR38 CR39 CR40 CR41\" citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e By 2005, approximately 44% of WTC rescue and recovery workers had developed GERD, which is 8.2-fold higher than the pre-9/11 prevalence, and more than double the general US population.\u003csup\u003e\u003cspan additionalcitationids=\"CR44 CR45\" citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e After WTC-PM exposure, GERD occurred more often in asthmatics.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Comorbid aerodigestive disease affected 51.4% of firefighters.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eGERD and BE are risk factors for esophageal adenocarcinomas (EAC).\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e Patients with BE face at least 30-fold higher risk of developing EAC than the general population.\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e Complications of GERD extend beyond malignancy and can adversely affect quality of life (QoL), impair productivity, and lifespan.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e GERD can incite or exacerbate co-morbidities such as allergies, sinusitis, chronic bronchitis, and asthma.\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e There is a 59.2% prevalence of GERD symptoms in patients with asthma compared to 38.1% in controls.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e GERD treatment in WTC responders with proton pump inhibitors (PPIs) have been found to increase risk of severe cognitive impairment.\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e Cognitive decline with PPI use has also been reported in the general population.\u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDespite numerous studies suggesting potential interdependence between airway and digestive diseases, the underlying causative factors and mechanisms remain unclear.\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e Biomarkers are often key to identifying causative pathways and mechanistic targets. While some studies have investigated serum, salivary, and microbial biomarkers of GERD, they are often not focused on the contribution of respiratory disease.\u003csup\u003e\u003cspan additionalcitationids=\"CR59\" citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe availability of clinical longitudinal phenotyping makes the WTC-PM exposed Fire Department of New York (FDNY) first responders cohort ideal for biomarker discovery.\u003csup\u003e10,22,28\u0026ndash;31,61\u0026minus;65\u003c/sup\u003e Notably, we have successfully identified biomarkers associated with GERD and BE in a pilot population with respiratory disease, facilitating the identification of biologically relevant immune pathways.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe diagnosis of GERD itself is a complex process that relies on subjective clinical symptoms and often necessitate objective but invasive testing such as endoscopy and 24-hour pH monitoring.\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e Those with endoscopic evidence of reflux may be entirely asymptomatic, potentially leading to under-diagnosis of patients at risk of BE and EAC.\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e,\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e Even with the most invasive procedures, the diagnosis of GERD can be elusive and plagued by poor sensitivity.\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn light of this, we propose to explore noninvasive biomarkers that could identify a population of aerodigestive disease, enabling better phenotyping of FDNY-WTC cohort with aerodigestive disease. In addition to their diagnostic utility, noninvasive biomarkers may direct future research into mechanisms and their downstream effects. GERD/BE biomarkers are also important to identify in the clinically silent presentations.\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e Additionally, we will identify novel non-invasive biomarkers of aerodigestive disease through a multi-OMIC approach. We will profile not only the metabolome and microbiome, but also exhaled, secreted, and blood biomarkers of aerodigestive disease, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo address a critical gap in the current literature, we will \u003cb\u003e1. Quantify noninvasive measures\u003c/b\u003e of aerodigestive disease (salivary pepsin, serum biomarkers/metabolome, fractional exhaled nitric oxide (FeNO), exhaled breath condensate (EBC), microbiome, cognitive measures and aerodigestive QoL/disease severity measures to phenotype and assess treatment efficacy. \u003cb\u003e2. Develop and optimize\u003c/b\u003e a noninvasive biomarker model of aerodigestive disease and also \u003cb\u003e3.\u003c/b\u003e determine the effect of aerodigestive disease on QoL, cognition and symptom phenotype.\u003c/p\u003e"},{"header":"METHODS/DESIGN","content":"\u003cp\u003e \u003cb\u003eStudy Design and Participants.\u003c/b\u003e The FDNY WTC-health program (WTC-HP) electronic medical record (EMR) will be used to obtain clinical variables such as age, gender, years of FDNY service, WTC site exposure level, and lung function measures, as previously described. \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan additionalcitationids=\"CR63 CR64\" citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e,\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e Our observational study is NYU IRB Approved # 21\u0026ndash;00679 and available at clinicaltrials.gov #NCT05216133. Study Definitions and Inclusion/Exclusion Criteria can be found in \u003cb\u003eTable\u0026nbsp;1.\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Population\u003c/b\u003e: \u003cem\u003eSource Cohort.\u003c/em\u003e All participants in the WTC-HP (n\u0026thinsp;=\u0026thinsp;14,976) were screened, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. \u003cem\u003eInclusion Criteria\u003c/em\u003e: i. Actively consented and enrolled member of the WTC-HP. ii. Pre-9/11 spirometry with Forced Expiratory Volume in 1 second (FEV\u003csub\u003e1\u003c/sub\u003e)\u0026thinsp;\u0026ge;\u0026thinsp;Lower Limit of Normal (LLN) iii. Male Firefighter status on 9/11 with exposure at the WTC-site and entry into WTC-HP before the site closure on 7/24/2002. \u003cem\u003eExclusion Criteria\u003c/em\u003e: i. lung disease prior to 9/11 as defined by positive methacholine or bronchodilator test, or FEV\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;LLN. ii. Not part of initial cohort in data extraction from August 1, 2017.\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e After all inclusion/exclusion criteria applied, the baseline cohort consists of n\u0026thinsp;=\u0026thinsp;4,192. \u003cem\u003eSub-cohort Development.\u003c/em\u003e A representative cohort of 20% was randomly selected (n\u0026thinsp;=\u0026thinsp;837; SPSS v. 28) from the above baseline cohort, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eRecruited Cohort\u003c/em\u003e will be developed to assess for noninvasive biomarkers. We will recruit a subset N\u0026thinsp;=\u0026thinsp;40/group (\u003cem\u003ei.\u003c/em\u003e AHR only \u003cem\u003eii.\u003c/em\u003e GERD only \u003cem\u003eiii.\u003c/em\u003e BE \u003cem\u003eiv.\u003c/em\u003e GERD/BE and AHR overlap or \u003cem\u003ev.\u003c/em\u003e No GERD nor AHR) from the sub-cohort, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Recruitment strategies will include: i. Direct mailings; ii. Email (potential participants will be sent the same IRB-approved recruitment message to their personal emails using end-to-end encryption; iii. Study website will include recruitment messages providing general information on the study and answers to frequently-asked questions. No direct communications will be made with participants through the website, and no PHI will be used or available within the study website; iv. Telephone contact. A description of the study will be provided to potential participants and, upon their expression of interest, the investigator will perform an eligibility screening. In addition to meeting the inclusion criteria as outlined above, participants should: i. have available serum from their first post 9/11 WTC-HP ii. not currently be receiving treatment for malignancy iii. have no limitations to a minimal risk blood draw iv. be willing and able to sign consent; and v. be able to attend a single-visit.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCase Status. WTC-AHR\u003c/b\u003e will be defined as having a positive methacholine (PC\u003csub\u003e200\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;16), or a positive bronchodilator response (by ATS/ERS guidelines with improvement of FEV\u003csub\u003e1\u003c/sub\u003e by 12% and at least 200mL) at least once post-9/11\u003csup\u003e73,74\u003c/sup\u003e and/or EMR diagnosis. \u003cb\u003eGERD\u003c/b\u003e will be defined as: biopsy-proven erosive esophagitis LA grade C or D; stricture or Barrett\u0026rsquo;s esophagus on endoscopy; and/or esophageal acid exposure time\u0026thinsp;\u0026gt;\u0026thinsp;6% on a pH or pH impedance study. GERD will also be defined on EMR diagnosis and/or PPIs, H\u003csub\u003e2\u003c/sub\u003e blockers, antacid, or surface agent use.\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e \u003cb\u003eBE\u003c/b\u003e, as a subset of GERD, will have any of the following additional inclusion criteria: biopsy-proven columnar epithelium lining\u0026thinsp;\u0026ge;\u0026thinsp;1cm of the distal esophagus with intestinal metaplasia characterized with goblet cells on histology; diagnosis on EMR, \u003cb\u003eTable\u0026nbsp;2-3\u003c/b\u003e.\u003csup\u003e\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e The recruited participants will be consented prior to any research activity and measurement visit via REDCap software or in person.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMeasurement Visit.\u003c/b\u003e Participant demographic information, medical history and medication history will be obtained. A physician will perform the physical examination, and verify that inclusion/exclusion criteria are met. Enrolled participants will undergo the following assessments.\u003c/p\u003e \u003cp\u003e \u003cb\u003eBlood Sampling.\u003c/b\u003e After at least an 8 hour fast, serum and plasma will be obtained, aliquoted and banked. Each stored specimen will be assigned a unique code to ensure proper identification and linkage to the respective participant. Aliquots from the fresh samples will be assayed for complete blood count (with differential) and chemistry panel. These data are already available for the banked samples. For all samples, lipid profile, metabolomics, and protein biomarker profiling will be performed.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e,\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSalivary Pepsin Assessment.\u003c/b\u003e 30mL sterile plastic tubes with 0.5 ml of 0.01M citric acid, adjusted to a pH of 2.5 (RD Biomed Ltd., Hull, UK), will be used by the participants to collect saliva in the AM (prior to brushing teeth, drinking or eating), 1h after finishing lunch, and 1h after finishing dinner.\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e,\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e Participants will be instructed to cough a few times prior to spitting into the tube to clear saliva from the back of the throat and then spit into the tube. The collected samples will be stored at 4\u0026deg;C and analyzed within 2 days. Salivary Pepsin will be analyzed using Peptest (RD Biomed Ltd., Hull, UK) as previously described.\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e Briefly, plastic tubes will be centrifuged at 4,000 rpm for 5 minutes, and 80\u0026micro;L of supernatant will be added to 240\u0026micro;L of migration butter solution for 10 seconds. 80\u0026micro;L of the mixture will be added to the well of the Peptest, which contains two unique human monoclonal antibodies that detect and capture pepsin protein (specific to pepsin-3), with a lower limit of detection of 16 ng/mL and an upper limit of 500 ng/mL. A salivary pepsin level of \u0026ge;\u0026thinsp;16 ng/mL will be considered positive. The sample will be processed in a Pepcube reader to quantify the pepsin concentration.\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSpirometry\u003c/b\u003e will be assessed using a KoKo PFT spirometer (nSpire Health Inc), and lung function assessment will be considered acceptable as per the ATS/ERS guidelines.\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e We will select the largest acceptable measures for electronic archiving. Each participant\u0026rsquo;s predicted percentage (%) will be calculated by NHANES III equations based on their age at examination, height, sex, and race.\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e,\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eFeNO\u003c/b\u003e will be quantified using NIOX VERO\u0026reg; (Aerocrine).\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e,\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e\u003c/sup\u003e Participants will be instructed to inhale to their total lung capacity via mouthpiece for 2\u0026ndash;3 seconds. Then, they will exhale at a flow rate of 0.05L/second. The device will provide results in parts per billion (ppb).\u003c/p\u003e \u003cp\u003e \u003cb\u003eExhaled breath condensate (EBC\u003c/b\u003e \u003cem\u003e)\u003c/em\u003e will be collected using RTubes (Respiratory Research, Inc., USA).\u003csup\u003e\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e\u003c/sup\u003e Approximately 1-2mL of EBC sample will be obtained after 10 min of quiet normal breathing.\u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e \u003cem\u003ePH measurement.\u003c/em\u003e EBC pH assay is extremely simple to perform, inexpensive, and robust, and can be easily processed on the day of collection.\u003csup\u003e\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e\u003c/sup\u003e EBC will be de-aerated of CO\u003csub\u003e2\u003c/sub\u003e by bubbling free argon gas (350ml/min) under a micro-pH reader (Orion PerpHecT micro-pH electrode) and stabilized pH will be recorded after approximately 3\u0026ndash;5 minutes.\u003csup\u003e\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e\u003c/sup\u003e Aliquots are then stored at -80⁰C and thawed only once prior to histamine and biomarker assessment.\u003c/p\u003e \u003cp\u003e \u003cb\u003eNaso/oropharyngeal microbiome.\u003c/b\u003e \u003cem\u003eCollection.\u003c/em\u003e Trained study team members will collect naso/oropharyngeal samples using commercially available kits (OMR-110 by DNA Genotek, Canada). Each naris will be swabbed in a circular fashion 10 times. The oropharyngeal sample will be collected by swabbing in the back of the throat in 10 circular motion to ensure sufficient swab collection. Each absorbent swab will be placed into a vial containing 1 mL of stabilizing liquid using aseptic technique. The sample will be treated with lyophilized Proteinase K, and incubated in the original vial at 50⁰C for 1 hour in a water bath prior to aliquoting for long-term storage at -80⁰C.\u003c/p\u003e \u003cp\u003e \u003cb\u003eQuality of Life, Aerodigestive Disease and End-Organ Effect Questionnaires.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eGastrointestinal impact\u003c/b\u003e will be assessed using with the Patient Assessment of Upper Gastrointestinal Disorders \u0026ndash; Quality of Life \u003cb\u003e(PAGI-QoL)\u003c/b\u003e and the Patient Assessment of Upper Gastrointestinal Disorders Symptom Severity Index \u003cb\u003e(PAGI-SYM).\u003c/b\u003e Both questionnaires use a 6-point Likert scale (MAPI Research Trust).\u003csup\u003e\u003cspan additionalcitationids=\"CR89 CR90\" citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eRespiratory and QoL assessment\u003c/b\u003e will utilize the Health-Related Quality of Life measures \u003cb\u003e(HRQL)\u003c/b\u003e\u003csup\u003e\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e\u003c/sup\u003e, St. George\u0026rsquo;s Respiratory Questionnaire (\u003cb\u003eSGRQ\u003c/b\u003e), and the Short-form-36 (\u003cb\u003eSF-36\u003c/b\u003e). HRQL assesses an individual's perceived physical and mental health. The SGRQ is a standardized, self-administered airways disease-specific questionnaire divided into three subscales- symptoms, activity, and impact.\u003csup\u003e\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e\u003c/sup\u003e SF-36 will capture supplemental information about their mental health, general health perception, emotional, and social role functioning.\u003csup\u003e\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eCognition\u003c/b\u003e will be assessed using the Montreal Cognitive Assessment \u003cem\u003e(\u003c/em\u003e\u003cb\u003eMoCA;\u003c/b\u003e version 8.1) and the Mini-Mental State Examination \u003cb\u003e(MMSE)\u003c/b\u003e. MMSE is a cognitive test used to evaluate early dementia.\u003csup\u003e\u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e,\u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e96\u003c/span\u003e\u003c/sup\u003e Combining MoCA and MMSE can improve diagnostic utility.\u003csup\u003e\u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e97\u003c/span\u003e\u003c/sup\u003e The MoCA will be administered by a trained/certified investigator. Members of our research team have completed MoCA training and certification through a validated MoCA cognition portal\u003csup\u003e\u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e98\u003c/span\u003e\u003c/sup\u003e (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mocacognition.com/\u003c/span\u003e\u003cspan address=\"https://mocacognition.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Similar to the MoCA, the MMSE assesses orientation, memory, visuospatial and language domains. Additionally, the MMSE evaluates comprehension, reading and writing.\u003csup\u003e\u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e99\u003c/span\u003e\u003c/sup\u003e The PI will thoroughly review all scores.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePower Analysis\u003c/b\u003e. A sample size of 40 cases for each group of GERD, AHR, AHR/GERD overlap, BE, and non-GERD/non-AHR Controls (all will be subsets of AIM 1 N\u0026thinsp;=\u0026thinsp;898 randomly selected cohort) achieves 80% power to detect difference as small as 0.78 SD with two-sample t-test at 0.01 significance level to account for multiple comparisons. This will allow us to achieve 80% power and significance of 0.05, based on prior studies with salivary pepsin test (personal communication with Dr. Peter Dettmar of Peptest), Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStatistical Analysis\u003c/b\u003e SPSS 28 (IBM) will facilitate database management and statistics. Continuous variables expressed as mean, standard deviation (SD) if normally distributed, and as median, inter-quartile range (IQR) if skewed. Two-sample t-test and ANOVA will compare continuous data. Count and proportions will summarize categorical data and Pearson-χ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e will compare categorical data. Multivariate binary logistic regression will estimate biomarker-disease relationship for case status as a binary outcome while adjusting for confounding. Cox proportional hazards model will evaluate the effects of biomarkers, smoking, and exposure on the hazard of developing WTC-GERD or BE over time. The maximum potential effectiveness of a biomarker will be calculated by Youden Index.\u003csup\u003e\u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e100\u003c/span\u003e\u003c/sup\u003e Goodness of fit, using the Hosmer-Lemeshow test. Survival curves compared by Log-rank test. Pearson \u0026#120594;\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e-test will compare SABA and LABA usage between GERD, AHR, AHR/GERD overlap, BE, and non-GERD or AHR controls. Significance will be assessed by p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for all statistical tests. Graphs will be created using Prism (v.10, GraphPad Software).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMissing data\u003c/strong\u003e \u003cp\u003eVariables with missing values in a small proportion of participants will be imputed using multiple imputation methods. To assess the missing at random assumption, we will evaluate the comparability between samples with missing data and those without. Sensitivity analysis will be performed by comparing the results obtained from the complete data analysis to the results obtained from multiple imputation.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eModel Building.\u003c/b\u003e We have previously identified key biomarkers using a machine learning approach.\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e We have further refined this analysis pipeline and will utilize this methodology to identify AHR, GERD, AHR/GERD overlap, and BE biomarkers. Specifically, we will utilize random forests (RF) of the filtered, normalized biomarkers. Models assessed via a modified hamming distance between variable importance rankings of models with identical hyper-parameters. A refined profile of the top 5% of important biomarkers by MDA will be included in a gradient-boosted tree model (xgboost package, R-Project) to build a classifier of AHR, GERD, AHR/GERD overlap, and BE. A random hyperparameter space search determined a final model that maximized AUC\u003csub\u003eROC\u003c/sub\u003e.\u003c/p\u003e \u003cp\u003eWe will also use linear mixed-effects models will be used to assess the temporal trend of biomarkers with time adjusting for confounders. The longitudinal biomarkers processes will be associated to risk of developing WTC-GERD/BE using the joint modeling technique.\u003csup\u003e\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e\u003c/sup\u003e The joint-modeling approach has become the primary method for analysis of longitudinal biomarker process and time-to-event outcome, and multiple R packages are available to implement the models. We will also consider a single index longitudinal model which enables us to reduce the dimensionality of multiple biomarkers and to evaluate joint effects of multiple biomarkers together to identify key risk factors. The single-index model incorporates longitudinal data to calculate hazard of each parameter as well as personalized dynamic risk for prognostication. Specifically, this will allow us to use a patient\u0026rsquo;s data from a single clinical exam to identify risk of GERD, AHR, overlap, or BE. Furthermore, this will allow the identification of false negatives and undertreated cases in the entire FDNY cohort.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003ePM exposure, a significant component of ambient and occupational exposures is a risk factor for aerodigestive disease (such as GERD and AHR) and is associated with approximately 7\u003cb\u003e-\u003c/b\u003emillion deaths annually. \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan additionalcitationids=\"CR103\" citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e\u003c/sup\u003e GERD is the most prevalent gastrointestinal disorder in the US, with an estimate as high as 30%.\u003csup\u003e66\u003c/sup\u003e Globally, the prevalence of GERD ranges from 10\u0026ndash;25%, with an increased risk in firefighters.\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e GERD is an independent risk factor in the development of BE which can lead to malignancy.\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDespite the similar risks, the understanding of the underlying pathophysiological interrelatedness between the aerodigestive diseases (AHR, GERD and BE) remains limited. Furthermore, GERD diagnosis and treatment has been invasive and costly. Therefore, our work is focused on identifying non-invasive biomarkers which may help identify at risk populations who may benefit from earlier intervention, targeted therapies and a further understanding of how their AHR is impacted by co-morbid GERD. The identification of non-invasive biomarkers of GERD/BE and the overlapping aerodigestive disease is crucial.\u003c/p\u003e \u003cp\u003eOur work will address the existing \u003cb\u003eknowledge gap\u003c/b\u003e in aerodigestive overlap and validate biomarkers of WTC-aerodigestive disease. Biomarkers of BE may also identify individuals at risk for neoplastic disease. These findings may have broader implications for populations with GERD and PM exposure. In contrast to currently used invasive testing, noninvasive testing offers diagnostic utility with reduced risk and can direct future research into mechanisms/downstream effects. We also systematically studied biomarkers of GERD/BE and defined some of the lacunae in the non-invasive aerodigestive biomarker literature.\u003csup\u003e\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e\u003c/sup\u003e Therefore, our Case-Control Observational Study is designed to sample a broad biomarker profile, \u003cb\u003eTable\u0026nbsp;3\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMicrobiome of the Gut/Lung Axis.\u003c/b\u003e Asthma susceptibility is influenced by the gut microbiome.\u003csup\u003e\u003cspan additionalcitationids=\"CR107 CR108 CR109 CR110\" citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e\u003c/sup\u003e Noninvasive collection sites that can approximate the pulmonary environment are of key interest. Studies have failed to show that the microbiomes of induced sputum were similar to the lung.\u003csup\u003e\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e,\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e\u003c/sup\u003e Noninvasively collected oropharyngeal and nasopharyngeal swabs in conjunction could approximate the lung microbiome.\u003csup\u003e\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e\u003c/sup\u003e Research has revealed that the esophageal microbiome undergoes alteration in individuals with GERD, BE, and other motility disorders.\u003csup\u003e\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e,\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e\u003c/sup\u003e Although these findings highlight the potential role of the microbiome studies in the diagnosis and therapeutic approaches for aerodigestive disease, further studies are needed and will be one of the key readouts planned in our study.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEBC\u003c/b\u003e analysis holds great promise in addressing unmet medical needs by expanding the portfolio of noninvasive assays for the multiple coexisting pathological mechanisms underlying respiratory disorders and GERD. Compounds identified in EBC include histamine, adenosine, ammonia, hydrogen peroxide, isoprostanes, leukotrienes, nitrogen oxides (NOx), peptides, cytokines, protons and various ions.\u003csup\u003e\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e\u003c/sup\u003e Histamine plays a vital role in digestion but elevated levels can contribute to the development of GERD.\u003csup\u003e\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e,\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSalivary pepsin\u003c/b\u003e has been studied in several GERD biomarker studies.\u003csup\u003e\u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e105\u003c/span\u003e\u003c/sup\u003e Due to the overlap of various reflux symptoms with other GI pathologies, the diagnosis of GERD can be challenging. However, salivary pepsin test offers a simple and convenient way for detecting reflux through salivary sample collection, providing quick and non-invasive results. Compared to other diagnostic modalities, this approach is time-efficient and requires much less effort.\u003csup\u003e\u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e\u003c/sup\u003e Moreover, pepsin measurements can identify pathologic reflux even in the absence of symptoms, and remain unaffected by the concurrent use of PPI. Several studies have demonstrated that pepsin detection in the sputum and/or saliva can be regarded as a sensitive, non-invasive method for the diagnosis of the proximal reflux of gastric contents, with a sensitivity ranged from 41.5\u0026ndash;73% and high specificity of 86.2 to 98.2%.\u003csup\u003e78,79\u003c/sup\u003e Despite these findings little is known about pepsin in the context of aerodigestive co-morbid disease.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFeNO\u003c/b\u003e, a biomarker of lung disease activity, will be a valuable measure in our population. FeNO is associated with airway hyperreactivity, and several studies demonstrated that FeNO is increased during obstructive exacerbations.\u003csup\u003e\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e\u003c/sup\u003e In our population with the aerodigestive overlap, FeNO levels can serve as an indicator of potential underlying AHR exacerbating symptoms of GERD. Thus, our work will also contribute to understand the role of FeNO in GERD, which remains inconclusive as only a limited number of studies have examined AHR/GERD.\u003csup\u003e121,122\u003c/sup\u003e The detrimental impact of even once-weekly episodes of GERD on quality of life\u003csup\u003e\u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e123\u003c/span\u003e\u003c/sup\u003e highlighted the importance of assessing aerodigestive disease quality of life and disease activity, therefore we will quantify the effects of GERD on these aspects through a validated set of questionnaires that will assess QoL, GERD specific symptoms and also cognitive involvement.\u003c/p\u003e \u003cp\u003eNon-invasive biomarkers of GERD, BE, AHR, treatment efficacy, and severity of symptoms will also be assessed in serum. This will allow us to measure Tumor Necrosis Factor (TNF-α), C-peptide, Fractalkine and Interferon-gamma-induced Protein 10 (IP-10) in our case cohort study to validate our prior pilot study.\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Serum samples will also be used to perform metabolomic profiling that will allow us to investigate metabolic correlates of aerodigestive disease. In addition, by validating serum biomarkers (proteins and metabolome) of GERD/BE, we seek to provide a biologically plausible target that enables early detection and facilitates therapeutic intervention in the PM exposed populations. Moreover, non-invasive phenotyping of WTC aerodigestive disease holds promise in improving the sensitivity and specificity of GERD diagnosis, enabling earlier identification of BE and facilitate the development of personalized therapy, thus to improve both the quality of life and overall health outcomes.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations and potential study concerns\u003c/b\u003e. We envision there are several limitations of our study. It is possible that no significant association exists between noninvasive biomarkers and aerodigestive diseases in the second decade after WTC exposure. The generalizability of our study could be impacted because the FDNY source cohort had no aerodigestive disease prior to 9/11 and had their serum samples banked within six months of 9/11, therefore making it less comparable to other cohorts. There may also be a subset of patients without history of GERD, but could still receive a clinical diagnosis of GERD based on questionnaires and/or elevated pepsin/biomarkers. For these patients, further follow-up with a gastroenterologist will be recommended. Additionally, we may use FeNO levels to identify the potential underlying AHR exacerbating symptoms associated with GERD. We will also account for the potential risk of loss to follow-up regarding the completion of the questionnaires and attendance of the in-person visit.\u003c/p\u003e \u003cp\u003eFurther investigation into the overlap of GERD/BE and AHR is envisioned to provide valuable insights in distinguishing disease phenotypes, demonstrating that biomarkers can predict GERD and/or BE. This work will have clinical implications for the diagnosis and treatment of WTC associated disease, as well as for the management of other patients in the WTC monitoring programs, and for the general population as intense PM exposures are occurring more frequently, for example through wild fire related PM. Our research will contribute to the development of a robust biomarker set with optimal explanatory power when applied to diverse cohorts.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003eAHR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003eAirway Hyper reactivity\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBADBURN\u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003eBiomarkers of Airway Disease, Barrett\u0026rsquo;s and Underdiagnosed\u0026nbsp;\u003cu\u003eR\u003c/u\u003eeflux \u003cu\u003eN\u003c/u\u003eoninvasively\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003eBody Mass Index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOPD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003eChronic Obstructive Pulmonary Disease\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDBP\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eDiastolic Blood Pressure\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDSMB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003eData and Safety Monitoring Board\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEAC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eesophageal adenocarcinomas\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eECG\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eElectrocardiogram\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFDNY\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eFire Department of New York\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFE\u003csub\u003eNO\u003c/sub\u003e\u003c/strong\u003eFractional Exhaled Nitric Oxide\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFEV\u003csub\u003e1\u003c/sub\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eForced Expiratory Volume in 1 second\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFVC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/strong\u003eForced Vital Capacity\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHRQL \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eHealth-Related Quality of Life\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eHealth Program\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIRB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003eInternal Review Board\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLI\u003c/strong\u003e\u0026nbsp; 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This study was approved by the Institutional Review Boards of Montefiore Medical Center (#07-09-320) and New York University (NYU IRB # 21-00679).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication.\u0026nbsp;\u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials.\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests.\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding.\u0026nbsp;\u003c/strong\u003eCDC/NIOSH U01-OH012069; U01-OH011300 and U01-OH011855; NIH/NIEHS, R01ES032808; Clinical Center of Excellence 200-2017-93426 and Data Center 200-2017-93326.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions.\u003c/strong\u003e \u003cstrong\u003eAN\u003c/strong\u003e was the primary investigator, had full access to all of the data in the study and takes responsibility for the integrity and the accuracy of the data analysis. \u003cstrong\u003eUJ, SK, SP, FF, ARK and AN\u003c/strong\u003e participated in study conception and design; \u003cstrong\u003eUJ, SP, SK, RZO, TS, DP and AN\u003c/strong\u003e were responsible for data collection;\u003cstrong\u003e\u0026nbsp;SK and AN\u003c/strong\u003e were responsible for data validation; \u003cstrong\u003eUJ, SP, SK, GG, and ML\u003c/strong\u003e participated in data analysis. All authors including (\u003cstrong\u003eDHK, AFZ, YL, AV, JZ, and GC\u003c/strong\u003e) participated in data interpretation, writing and revision of the report and approval of the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements.\u003c/strong\u003e The authors would like to thank the FDNY first responders for their bravery and for taking part in our study,\u0026nbsp;\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSeo HS, Hong J, Jung J. Relationship of meteorological factors and air pollutants with medical care utilization for gastroesophageal reflux disease in urban area. World J Gastroenterol. 2020;26:6074\u0026ndash;86.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaffney KF. Infant exposure to environmental tobacco smoke. 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Aliment Pharm Ther. 2006;23:1725\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Air Pollutants, Airway hyperreactivity, Ambient Particulate Matter, Barrett's Esophagus, Gastro-Esophageal Reflux Disease, Particulate, Aerodigestive","lastPublishedDoi":"10.21203/rs.3.rs-4355584/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4355584/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBACKGROUND.\u003c/h2\u003e \u003cp\u003eParticulate 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\u0026rsquo;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.\u003c/p\u003e\u003ch2\u003eMETHODS.\u003c/h2\u003e \u003cp\u003eOur observational case-cohort study will leverage the longitudinally phenotyped Fire Department of New York (FDNY)-WTC exposed cohort to identify \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eB\u003c/span\u003e\u003cem\u003eiomarkers of\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eA\u003c/span\u003e\u003cem\u003eirway\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eD\u003c/span\u003e\u003cem\u003eisease\u003c/em\u003e, \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eB\u003c/span\u003e\u003cem\u003earrett\u0026rsquo;s and\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eU\u003c/span\u003e\u003cem\u003enderdiagnosed\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eR\u003c/span\u003e\u003cem\u003eeflux\u003c/em\u003e \u003cspan type=\"ItalicUnderline\" class=\"ItalicUnderline\" name=\"Emphasis\"\u003eN\u003c/span\u003e\u003cem\u003eoninvasively (BAD-BURN).\u003c/em\u003e Our study population consists of n\u0026thinsp;=\u0026thinsp;4,192 individuals from which we have randomly selected a sub-cohort control group (n\u0026thinsp;=\u0026thinsp;837). We will then recruit subgroups of \u003cem\u003ei.\u003c/em\u003e AHR only \u003cem\u003eii.\u003c/em\u003e GERD only \u003cem\u003eiii.\u003c/em\u003e BE \u003cem\u003eiv.\u003c/em\u003e GERD/BE and AHR overlap or \u003cem\u003ev.\u003c/em\u003e 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.\u003c/p\u003e\u003ch2\u003eDISCUSSION.\u003c/h2\u003e \u003cp\u003eAlthough 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.\u003c/p\u003e\u003ch2\u003eTRIAL REGISTRATION:\u003c/h2\u003e \u003cp\u003eClinicalTrials.gov Identifier: NCT05216133; January 18, 2022.\u003c/p\u003e","manuscriptTitle":"Biomarkers of Airway Disease, Barrett’s and Underdiagnosed Reflux Noninvasively (BAD-BURN): a Case-Control Observational Study Protocol","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-15 15:49:04","doi":"10.21203/rs.3.rs-4355584/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-14T10:29:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-08T05:43:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-07T14:04:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Gastroenterology","date":"2024-05-01T18:15:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-gastroenterology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmge","sideBox":"Learn more about [BMC Gastroenterology](http://bmcgastroenterol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmge/default.aspx","title":"BMC Gastroenterology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a53dbf06-112f-48f1-bd46-3341fc977c0f","owner":[],"postedDate":"May 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-12T16:08:56+00:00","versionOfRecord":{"articleIdentity":"rs-4355584","link":"https://doi.org/10.1186/s12876-024-03294-9","journal":{"identity":"bmc-gastroenterology","isVorOnly":false,"title":"BMC Gastroenterology"},"publishedOn":"2024-08-09 15:57:32","publishedOnDateReadable":"August 9th, 2024"},"versionCreatedAt":"2024-05-15 15:49:04","video":"","vorDoi":"10.1186/s12876-024-03294-9","vorDoiUrl":"https://doi.org/10.1186/s12876-024-03294-9","workflowStages":[]},"version":"v1","identity":"rs-4355584","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4355584","identity":"rs-4355584","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}