Good morning, everyone, and thank you all for coming. My name is Tom Alexander, and I'm going to talk about our abstract title, Mosaic Nation, Air Trapping Veterans, Unexplained Dyspnea. It may be driven primarily by a vascular component. Just a quick disclosure, don't really have too much, just that the views presented here are my own and not the US government or the VA. So following deployment, a lot of veterans have increased endorsement of respiratory concerns. And while the exact cause of that is being highly researched today, you could say that they're extremely vulnerable and increasingly susceptible to these respiratory conditions because of all the stresses they go through during deployment. What's been particularly unique about this group and kind of frustrating is that a lot of veterans have persistent symptoms but have within normal lung function testings. And one potential reason for that might be the fact that your PFTs are just not sensitive enough to pick up what you need to pick up, especially if you're suspecting some small airway involvement. So our group started to look at HRCT scans in our clinical veterans. So we looked at about 200 veterans and reviewed their scans and found that about 50% of them had this mosaic attenuation and or air trapping, which is highly associated with small airway disease. So for this abstract, we thought, all right, let's take a look at their PFTs and also more sensitive testing for FOTs to see if there's any differences between the group with that air trapping pattern. And those with no abnormal finding in their CT but still have complaints of respiratory symptoms. While we expect those PFT variables to be pretty similar between the group, we thought introducing a more sensitive testing will reflect the differences seen in our HRCT findings. So really quick, we went through 200 HRCTs and selected 98 veterans that met our grouping criteria. We found 20 veterans that had no abnormal findings and called them CT normal or our control group. And then we found 78 veterans with that CT trap pattern, mosaic attenuation, or air trapping. We kept our analysis pretty simple. We was a simple T-test or a man with a U-test based on normality. And for the most part, I reported effect sizes here. We also re-ran all of our analysis for a match group, match for age, BMI, pack years, and sex. We were able to find 15 veterans in that control CT normal group and matched it to 15 veterans in our CT trap group. Here we have your general characteristics of the entire group of 98 veterans. Both group comprised predominantly of white men in their 40s, similar height and weight. Only significant difference, of course, is deployment length, where the CT trap group had a couple of months longer deployment than the CT normal group. Now I'm just going to run through our lung function testing results. For the most part, all the remaining slides are structured similarly, where you have tables showing the raw mean values. And it's color-coded based on effect size, meaning the darker the shading, the higher the effect. The figures in the graphs there are percent predicted, where blue is always CT normal and your yellow is your CT trap. So if you look at lung volumes, you can see that it's pretty normal. You see a very within normal range, looking at percent predicted for both groups, and there was no significant difference between both groups when you look at the mean values. One thing to note, though, is that RVTLC and FRC over TLC, which could be an indicator of air trapping, was a little elevated for both groups. And here we have the spirometry, again, this is the unmatched group, and similar story, where you have similar percent predicted and mean values between both of the groups. Again, one thing to note, though, is in the CT normal, you have a higher percentage of veterans that have an FEV1 or FEC ratio below the lower limit of normal, despite not having any signs of air trapping in their CT scan. DLCO was actually the only thing that was significantly different between two groups, where our CT trap group had a significantly lower DLCO. This is something we've seen before, where veterans come in with an isolated reduction of DLCO, which is a pretty rare phenomenon in the normal population, and the prognosis is not usually too well. If you look at the graph there, you can see that the CT trap group, there's a couple of veterans still below that 75% lower, or 75% predicted, which is pretty low, and shows some sort of issues of profusion. And finally, this is the FOT. So this was that more sensitive testing we were talking about, and we didn't see any difference between the two groups. They were pretty much overlapped for every single variable we looked at. What was interesting to note, though, is that both groups had a higher resistant R4 than R20, and both groups had a majority of the veterans with the AX over the upper limit of normal. That's a signature of small airway disease and some air trapping, regardless of what the HRCT scans showed. And now I'm going to just quickly go through our match results. For the most part, there really wasn't any difference. Again, the sample size here is much lower. It's 15 on each group. And you see a similar story, where your lung volumes are within normal, and there is no significant difference between the two groups. Same thing with spirometry. Although you do see a higher burst off in the CT normal groups, a little more pronounced when it was matched, where you've got 27 veterans with the FEU1 less than lower limit of normal. We lost a significance in the DLCL, but there's still a moderate difference between the two groups. And you can see in the graph that the mean percent predicted is a little lower than your CT normal group. And our FOT was exactly the same, where both groups showed signs of air trapping and was not different, regardless of what their HRCT showed. So very quickly, to wrap it up, when we reviewed our HRCT scan, we saw that mosaic attenuation air trapping was commonly observed in our veterans. But despite those differences in their HRCT, their PFT and FOTs were relatively similar. Both groups showed some signs of air trapping and small airway disease. When you look at RVTLC and FRCTLC, and more effectively, the FOT showed air trapping and small airway disease in both groups. This along with the fact that DLCL is only valid at a significant difference, that is to say that it might be, what the changes you see in HRCTs may be more reflective of vessel involvement as opposed to small airways. And with that, I'm going to say thank you so much, and a quick shout out to the rest of my team. They are amazing and do all the hard work. Come to Hawaii and do this presentation. That's all I've got. Good morning, everybody. I am Steven Stoffel. I am currently one of the first year pulmonary critical care fellows at Brook Army Medical Center in San Antonio, Texas. So just to go into some disclosures for our study that we did, Dr. Morris is a paid speaker for Janssen, though other authors do not have any significant conflicts of interest. As well, we are employees of the DOD, DHA, and BAMC, but these do not reflect the views of those government entities. So going along with our previous presentation as well, multiple, many active duty service members who return from deployment have been known to develop chronic respiratory symptoms to include dyspnea with exertion, dyspnea, and reduced exercise tolerance. These deployments are predominantly in Southwest Asia, and they are to be exposed to higher levels of ambient particulate matter, such as dust, smoke, pollution, vehicle exhausts. So our study was trying to determine exactly if multiple deployments would be associated with a decrement in both PFTs and CPETs. A study that was published in Chess in 2020 was the SAMP3 trial, which was a prospective evaluation of these new respiratory symptoms from military personnel that were returning from Operation Enduring Freedom as well as Operation Iraqi Freedom as well. During the study, they noted that the predominant etiologies that they were able to assess for this group was exertional dyspnea, about 32 percent, as well as asthma and 23, airway hyper-responsiveness, and some upper airway disorders. Of note, only about 2 percent were noted to have any evidence of diffuse lung disease. There were also numerous comorbidities that were seen, such as GERD, obstructive sleep apnea, PTSD, and traumatic brain injury. This is an initial breakdown from SAMP3, just showing the breakdown of all of the different etiologies that were seen of note, and about 50 percent of this group had either exertional dyspnea or asthma as their predominant etiology. This is a breakdown in SAMP3 with regards to this group's, again, about 380 participants with their PFT breakdown. For exertional dyspnea, again, had relatively normal PFTs. In the asthma group, you can notice a decrease in the FEV1 as well as FEV1-FEC ratio, which is pretty consistent with the diagnosis for asthma. So again, our clinical question was, do multiple deployments to Southwest Asia have any decremental effects on both PFTs or CPETs? So going into our methods, we were able to recruit military personnel who underwent deployments to this area. They underwent a standard baseline PFT testing as well as CPET, and then we also had a age-matched control group that underwent the same testing. In total, we had 1,045 participants, which included 585 active duty members, as well as 460 non-military participants. We have a slightly older age of 53.8, which was average for SAMP3 was like 38 to 39. We were 92% predominantly male, and of note, the average number of deployments was five, with average number of months deployed being 37.6. As far as the breakdown for the initial pulmonary function testing for these groups, again, really didn't show any substantial difference. FEV1-FEC as well as the ratio were all within about 2% of each other and were well above the ranges for normal. This is the initial breakdown for the CPETs. Again, we see that overall most of the values are pretty even between both of the active duty members as well as the non-deployer group. We did note a slightly increased VO2max for the active duty service members that were tested, though it was not statistically significant given the p-value of 0.061. Otherwise, the anaerobic threshold as well as the VE and VV were all pretty similar, but were, again, well above the range for normal. So as far as the discussion, the SAMP3 trial did help to be able to define the etiologies for active duty members who returned from deployment with symptoms. We do need long-term outcomes to be able to evaluate the chronic health of these service members that are exposed to burn pits and geologic dust as they return from deployment. Most of the previous studies were all relatively short-term with about six- to nine-month deployments and we don't have as much data long-term for these groups. This study overall did not show any significant decrement in both PFTs or CPETs. Of note, most of the patients in our trial were asymptomatic, so they didn't have any symptoms at baseline. So comparing it to the Stampede group who underwent CPETs as well, so now trying to switch to a group that does have symptoms, there is noted decrease in both exercise time as well as VO2 max in this group to some extent. So there appears there's something going on as far as the exercise tolerance in this group of symptomatic active duty service members. So as far as the conclusions, so long-term PFT and CPET data didn't show any significant changes in our group though. In asymptomatic versus symptomatic, there may be changes in CPETs long-term for these service members and further subgroup analysis needs to be done to be able to help delineate those that would be able to develop symptoms of this or try to figure out an exact etiology as far as why there is such a substantial reduce in those. And as far as our study limitations, we did have a predominant male cohort. Our cohort was older than Stampede 3, and then we had a pretty large standard deviation as well as the variance throughout most of the PFT to CPET values, even in both the cohort and the control group. So looking forward, again, hopefully we'll be able to get more studies to be able to compare both the symptomatic as well as asymptomatic active duty service members and be able to monitor them long-term, be able to hone down a definitive diagnosis for them and treatment. And thank you. Next up, we'll have Dr. Raichan Nahar discussing initial HRCT findings and temporal changes in military veterans evaluated for unexplained dyspnea at a VA national specialty clinic. Hello, everyone. I'm Raichan Nahar, a pulmonary and critical care medicine fellow at Rutgers New Jersey Medical School, and I have no disclosures. So just for your background, in high-risk population, the United States Preventive Services and Task Force guidelines recommend annual low-dose CAT scan of the chest for patients who are of the age 50 to 80 years and have a 20-pack-year history of smoking, either current or within the past 15 years. And our veterans have multiple military environmental exposures, and these occupational exposures, it is unclear if it puts them to a higher risk for developing lung cancer. Pulmonary nodules can be found on CAT scans of these veterans who are, you know, presented to a national specialty clinic with unexplained dyspnea, and evolution of these incidental pulmonary nodules have not been studied so far. So ours, in New Jersey, is a war-related illness and injury study center, one of the three centers in the United States, and one of the only airborne hazards and bone pit exposure center of excellence. Our study is a retrospective cohort study, a medical chart review of the veterans that were deployed for an average of 14 months to Southwest Asia and Afghanistan. Southwest Asia and Afghanistan with chronic unexplained respiratory symptoms. The study period is a 10-year period from January 2010 to December 2020, and they presented to our VA clinic for the unexplained dyspnea workup, where part of the workup was to get a high-resolution CAT scan of the chest. So we looked at the initial CT chest findings on these patients, and if there were presence of, we looked for the presence of nodules or other CT chest abnormalities, and then if they had the nodules, number one, if they had a repeat CT scan as a follow-up, and what was the evolution of these nodules. So we had 192 veterans part of this study, and 13% were female, which is approximate female veteran population in the United States. The mean age at evaluation was 44.8 years. The initial evolution timeline post-deployment was about 14.7 years, and most of these veterans, 95%, had exposure to either the bone pits or dust and sand, the airborne hazards. And 50% of the veterans had nicotine use, an average 8.7 pack-year history of tobacco use. So on this histogram, the initial CT chest findings of these veterans are described, and as you can see, 47% of the veterans had air trapping, and about 32% of the veterans, which is 62 out of 192, had pulmonary nodules. Going into the details about the pulmonary nodules on the initial CT chest findings, 84% had smaller nodules, less than six millimeter, either single or multiple nodules, and then there were four veterans who had a six to eight millimeter nodule, and five of them had a larger nodule of eight to 30 millimeter, and then one of them had lung mass. After this, we looked at the follow-up CT chest on the veterans, and for any reason, about 44% of the veterans had a repeat CT chest, and 68% of the veterans who had pulmonary nodules on the initial CAT scan had a follow-up CAT scan, and the average time period of follow-up CAT scan was about 30.6 months. So, of all cause-repeat CAT scans, that is 44%, 84 veterans out of 192, 29 veterans had no nodules on the initial scan or the repeat scan, 15 veterans had resolution of the previously found nodules, 22 veterans had stable nodules, four of the veterans had an increase in either the size or the number of the nodules, 13 veterans had newer nodules, and one of them had adenoparsinoma of the lung. And this is the distribution of the nodules on the follow-up CT chest. As you can see, majority of the veterans, 76%, still have smaller nodules, less than six mm, either single or multiple, and then three of the veterans had nodules six to eight mm, two of them had multiple, greater than six mm nodules, and five had nodules which were larger, about eight to 13 mm. The veterans who had either increase in the size or number of the nodules, one of the veterans had a nodule of less than six mm initially, and then had a new ground glass opacity, or a nodule about six to eight mm, sorry, eight to 30 mm on the repeat scan. Another had multiple, greater than six mm nodules. The veteran who had the nodule of the six to eight mm size had a larger nodule fall into the category of eight to 30 mm size, it was about a centimeter, and then had another CAT scan later on, which had stable nodule size. And then one of the veterans who had multiple, less than six mm nodule, had more than six mm multiple nodules, also had mediastinal lymphadenopathy, and then had a biopsy diagnosis of sarcoidosis. On the initial CAT scan, the veterans who had the larger nodules of the size eight to 30 mm, which would be concerning size, as you can see, one of them had a diagnosis of granulomatosis with polyangiitis, another had the adenocarcinoma of the lung, one of the veterans had stable findings, the nodule resolved in one veteran, and then other had the diagnosis of sarcoidosis. And the veteran who had the lung mass on the initial CT turned out to be sarcoidosis. So in summary, 30% of the veterans had incidental pulmonary nodules on the CT, which is similar to the civilian population. A third of our sample with incidental nodules at initial evaluation did not have a follow-up CT test in the VA facility at the time of the review, which is one of the limitations of our study, as we could not trace the follow-up CT scans that were performed outside in the community. These veterans do have non-resolving nodules and new nodularity, which needs continued surveillance and attention. And then clinicians are encouraged to adhere to the current nodule management guidelines. Certainly further studies are needed with the larger population and more longitudinal study with serial CAT scans to further evaluate the evolution of nodules in these veterans. Thank you so much for attending the talk. And please wait for the questions. Next up, we'll have Rachel Lamb, who will be discussing diet and microbiome with particular matter-exposed firefighters who have lung disease, the Firehouse Randomized Clinical Trial. Okay, good morning. My name's Rachel Lamb. I am a member of the Nolan Lab at NYU Grossman School of Medicine. And I'm also a medical student at Loyola Stritch School of Medicine. And I'm here to talk about diet and the microbiome in World Trade Center particulate matter-exposed firefighters with lung disease, Firehouse Randomized Clinical Trial. And we had CDC and NIOSH funding. And so first, objectives, what we're gonna talk about today. So some background about metabolic syndrome and lung disease methods, how we collected microbiome data. And in the Firehouse trial, some results about some interesting findings that we found and conclusions of what we took away from our trial and microbiome. So some background first. So metabolic syndrome, or what we call Metsin for short, it affects more than 30% of adults in the United States. Characteristics are routinely measured, generalizable, and validated biomarkers of cardiovascular disease. And it predicts future World Trade Center lung injury, which is when FEV1 is less than a lower limit of normal in FDNY World Trade Center-exposed firefighters. And microbiome, it plays a role in mediating inflammatory responses in the lung. And so methods. So a little bit about Firehouse Randomized Clinical Trial. So it stands for Food Intake Restriction for Health Outcome Support and Education. And it uses technologically supported educational and behavioral intervention. We targeted calorie restriction for weight loss while following a Mediterranean-type style dietary pattern. And so we intended to randomize 64 in intervention, 64 in control, and then collected all these data points. And in particular, today we're gonna talk about the microbiome portion of it. And so a little bit more. It's a six-month Mediterranean-type dietary intervention. We wanted to find a change in BMI of one to two. And using a multidisciplinary approach, we used cloud-based self-monitoring, social cognitive therapy, and standardized education with more details on the right-hand side. And so in particular, the microbiome portion, we collect a stool at baseline and at six months after intervention using omni-gene gut kits. And for the pilot study, we did five for low-calorie Mediterranean, the low-cal med arm, and five for usual care. And then for the validation cohort, we used 15 for the low-cal med and 16 in usual care. And then for analysis, we used booster shot shotgun sequencing from Diversagen and the QIIME and SPSS software and other further things. And so results, what did we find? So in particular for firehouse, we were able to stop the study early because we had reached predetermined stop criteria. And so we randomized 46 in the low-cal med and 43 in the usual care. And then in the middle, you see some of the data points that we measured, like spirometry, vitals, and some questionnaires. And for outcomes, what we found was that there was a significant decrease in BMI in the low-cal med arm compared to usual care. And then there was increase in FEV1 in the low-cal med arm while the usual care participants had no changes. And then we also had improved vascular health in our intervention arm, specifically in the diastolic blood pressure, improved dietary habits in the low-cal med arm, and some decrease in calories, fat and calories from sweets. And then, so we also measured other points, one called alpha diversity, which is the measure of microbiome diversity applicable to single sample. And the Shannon Diversity Index is a specific metric of alpha diversity. And it is defined as how diverse the species in a given community are. And we found that individual microbiome community diversity did not differ between arms at either time point in both pilot and validation study, but decreased across time for both arms. And then in our pilot study, we were also able to measure beta diversity, which is a measure of microbiome similarity or dissimilarity of two communities and ecosystems. And so we found that microbial community composition did not differ between arms at either time point or between time points. And so we were able to replicate some of our pilot results in our validation study as well, but here I'm just focusing on the validation study. And so in our low-cal med arm, we found this decrease in this family listed on the screen, and then also increase in these species, in particular the Bacteriords ovatus species. And then in usual care, we had a decrease in the order genus and species listed on the screen. And I just wanted to talk a little bit about on this particular slide, the Bacteriords ovatus species, and kind of correlating changes in BMI with microbiome. And in particular, we found that when incorporating health measures with microbiome analysis, a reduction in BMI was associated with an increase in the abundance of Bacteriords ovatus. And this was very interesting to us because in literature, we found that in a nutritional intervention in a high fat consuming murine model, mice scavenged with B ovatus had fewer negative health effects. And so conclusions. So overall, we found that in our validation cohort, the Bacteriords ovatus was increased in the low-cal med arm after six months. And this bacteria species is associated with fewer negative health effects. And in that study I talked about in the literature, we found that increases in that Bacteriords ovatus was associated with BMI reductions, decreased serum LDL-C and triglyceride levels in that murine model. And so future studies that we are going to do will assess microbiome associations with clinical outcomes. So some implications. So our firehouse randomized control trial focuses on multi-omic comprehensive assessment of World Trade Center particulate matter exposure associated World Trade Center lung disease and leverages the longitudinally phenotyped FDMY cohort. So not only provides a pathophysiological insight, but also lays the groundwork for future therapeutics. And so just to sum it up, we're going to continue working on looking at microbiome, methylome, genome and metabolome, as well as in the context of our firehouse randomized control trial with all these other data points to then kind of lay the groundwork for expanding the findings that we found in the trial, as well as how it can help the health of other affected cohorts and go from there. And I would like to thank the FDMY first responders for their bravery, dedication, as well as all the other members listed here. Thank you so much. Thank you. Next, we have Dr. Podhuri, who is going to give us a discussion on short acting beta agonists and steroids associated with development of aerodigestive disease, particulate matter exposed firefighters. Thank you. Thanks for your patience. Good morning, everyone. I am Sanjiti Podhuri, and I'm currently a postdoctoral research fellow at the NYU School of Medicine. I am also applying for the internal medicine residency match this year. I have nothing to disclose. So today, we're going to be discussing about how the use of short acting beta agonists and steroids are associated with the development of aerodigestive diseases in particulate matter exposed firefighters. So I'm going to start off by giving a background on how WTC, particulate matter exposure, is associated with development of GERD and Barrett's esophagus, followed by a little background on the longitudinal follow up on these firefighters. We're then going to discuss the clinical implications and the future work at our lab. So a lot of our firefighters were predisposed to a bunch of conditions after their exposure to the World Trade Center particulate matter. These include airway hyperreactivity, cancer, GERD, rhinosinusitis, and other mental health conditions. So these firefighters have been followed longitudinally since their exposure in 2001 as a part of their World Trade Center health program. And by 2005, almost 44% of these rescue workers had developed GERD, which is 8.2 times its pre-911 prevalence and 2.2 times the prevalence when compared to the general US population. A lot of, most of these firefighters had coexisting airway hyperreactivity. And you can see on the right, the graph shows how the incidence of GERD went up within two to three years of exposure to particulate matter in these firefighters. A lot of investigators are now studying the interdependence between airway and digestive diseases. And our pilot study that was published in Scientific Reports in 2018 showed how SABA, which is short-acting beta agonist use, was associated with development of GERD. So the purpose is to validate the risk of respiratory medication use in these WTCPM exposed firefighters with the development, with EHR on developing GERD and BARETs. So in our study, GERD was defined as having an EMR diagnosis or with the use of proton pump inhibitors or H2 blockers or surface agent use. BARETs was based on EMR diagnosis. Airway hyperreactivity was based on positive methacholine or bronchodilator testing and or EMR diagnosis. Usage of either prednisone or dexamethasone was defined as steroid use. So there are about 13,000 firefighters that are enrolled in the WTC health program cohort. And about 4,000 of these had recently consented, had a normal lung function prior to 9-11, and were exposed to the WTC site within two weeks of 9-11. We further subdivided the sub-cohort into GERD or no GERD. And the GERD population was further subcategorized as having either GERD or BARETs only or in GERD and BARETs with EHR. So most of these firefighters were male, Caucasian, and had a mean age of 39 on 9-11. 60.5% of these firefighters developed GERD and about 10% had BARETs. So from our analysis, we saw that SABA use was associated with GERD in 44% of firefighters and 47% of SABA users had BARETs. Similarly, in case of steroids, about 24% of these firefighters developed GERD and 29% had BARETs. So we saw that there was an increased odds of developing GERD by four and BARETs by 1.97 in SABA users. And in case of steroids, GERD went up by 4.65 and BARETs by 2.27. We also saw that there was an association with respect to exposure. So firefighters who had arrived at the site in the morning of 9-11 had an increased risk by 36% compared to those who had arrived in the afternoon. Similarly, in case of steroids, those who arrived in the morning had increased odds of developing GERD by 40.8%. In conclusion, in a population with high PM exposure, SABA and steroid use is associated with higher risk of developing GERD. We're trying to study further into this overlap between GERD, BARETs, and airway hyperreactivity and trying to distinguish different phenotypes of these diseases. Future studies will also include an assessment as to the use of inhaler use and its role in aerodigestive diseases and analysis of non-invasive biomarkers that can predict GERD and BARETs. We are currently enrolling a sub-cohort into our observational study that is investigating non-invasive biomarkers of GERD and BARETs and airway hyperreactivity. I'd like to thank the FDNY first responders for their bravery and dedication, the other members of the WTC Health Program, and other lab members that work on this project. Thank you.

short-acting beta-agonists

steroids

aerodigestive diseases

gastroesophageal reflux disease

GERD

Barrett's esophagus

particulate matter-exposed firefighters