Abstract 200: Risk Factors Positively Associated with Annual Growth Rate of Brain Aneurysms

Introduction: Previous studies have shown that unruptured intracranial aneurysm (UIA) growth and rupture are strongly associated with each other, with an increasing number of aneurysms followed clinically, especially UIA smaller than 7 mm. Hypothesis: Patient-specific and aneurysm-specific clinical and demographic features can predict growth and growth rates of UIA. Methods: We studied a cohort of 293 individuals diagnosed with a total of 409 intracranial aneurysms followed for an average of 27.4 months. Associations with aneurysm growth and growth rate were identified for both patient- and aneurysm-specific variables. Growth was defined as a size increase greater than 0.6 mm, with growth rate (mm/year) determined from the change in size of the aneurysm between the first and last measurement. Results: Mean initial size at diagnosis was significantly associated with risk of growth (OR: 1.09, 95% CI: 1.01-1.18, p=0.036), as was diagnosis of multiple aneurysms (OR: 2.01, 95% CI: 1.00-4.04, p=0.048) and having a positive family history (OR: 4.25, 95% CI: 1.18-15.3, p=0.041). Diagnosis of coronary artery disease (CAD) (p&lt;0.001), diabetes (p=0.041), and gender (p=0.014) were significant for growth rate. Differences were observed for aneurysms located in different vessels, with an increased occurrence of growth at M-Bifurcation (p=0.015 vs. other MCA sites) and a high growth rate for those located in the BA trunk (p=0.0033 vs. other VABA sites). Conclusions: This analysis takes advantage of a large longitudinal cohort with multiple follow-up measurements to provide further insight regarding the characteristics of UIA growth behavior. While our data further confirm that aneurysm rupture and growth share a similar set of risk factors (size, multiplicity and family history), we additionally that found patients with CAD or diabetes had a higher aneurysm growth rate, and therefore might require more frequent follow up. </jats:p

Using Geospatial Methods in Childhood Lead Poisoning Prevention Programs

In this paper, we explore how the construction and analysis of geographically referenced data can improve outcomes for children at risk of lead exposure. We discuss the history of how children were identified for lead testing and lead intervention (both medical and housing) over time, as well as the shortcomings of the United States’ current approach. We then suggest ways that geospatial approaches can improve lead testing and intervention programs, especially in settings with limited information or financial resources.</p

Adverse Health Outcomes Following Hurricane Harvey: A Comparison of Remotely‐Sensed and Self‐Reported Flood Exposure Estimates

Abstract Remotely sensed inundation may help to rapidly identify areas in need of aid during and following floods. Here we evaluate the utility of daily remotely sensed flood inundation measures and estimate their congruence with self‐reported home flooding and health outcomes collected via the Texas Flood Registry (TFR) following Hurricane Harvey. Daily flood inundation for 14 days following the landfall of Hurricane Harvey was acquired from FloodScan. Flood exposure, including number of days flooded and flood depth was assigned to geocoded home addresses of TFR respondents (N = 18,920 from 47 counties). Discordance between remotely‐sensed flooding and self‐reported home flooding was measured. Modified Poisson regression models were implemented to estimate risk ratios (RRs) for adverse health outcomes following flood exposure, controlling for potential individual level confounders. Respondents whose home was in a flooded area based on remotely‐sensed data were more likely to report injury (RR = 1.5, 95% CI: 1.27–1.77), concentration problems (1.36, 95% CI: 1.25–1.49), skin rash (1.31, 95% CI: 1.15–1.48), illness (1.29, 95% CI: 1.17–1.43), headaches (1.09, 95% CI: 1.03–1.16), and runny nose (1.07, 95% CI: 1.03–1.11) compared to respondents whose home was not flooded. Effect sizes were larger when exposure was estimated using respondent‐reported home flooding. Near‐real time remote sensing‐based flood products may help to prioritize areas in need of assistance when on the ground measures are not accessible

Association between Residential Distance to Airport and Blood Lead Levels in Children under 6 Living in North Carolina, 1992-2015

Even with progress in lead poisoning prevention, research has consistently shown there is no safe blood lead level (BLL) for children.1 Behavioral and cognitive deficits are associated with lead exposure, even at low levels.2 Unfortunately, many piston-engine aircraft are still fueled by leaded aviation gas (avgas).The US Environmental Protection Agency (EPA) estimates that∼5.2million people live within500m of an airport where avgas is used.3 Our past research in six North Carolina (NC) counties indicates that children living within500m of airports where avgas is used have∼4% higher BLLs than children who lived beyond2,000m (reference group); the association between avgas and children’s BLLs was still detectable at1,000m.4 Building on this work, this study investigates the relationship between avgas and BLLs in children across all 100 NC counties.In October 2023, the EPA finalized an endangerment finding as the first step in using its authority to regulate the use of avgas. EPA is now required by the Clean Air Act to propose and promulgate regulatory standards for lead emissions from certain aircraft engines. Moreover, the Federal Aviation Administration (FAA) must propose avgas that will control or eliminate lead emissions. In this paper, we provide evidence that is relevant to the EPA’s future regulatory proposals.</p

Abstract 853: <i>GPX4</i> Gene Expression is Dose-responsive to Doxorubicin Exposure in iPSC-Cardiomyocytes and Correlated With Mitochondrial Function

Impaired mitochondrial function has been implicated as a mechanism of doxorubicin-induced cardiotoxicity, however the precise genes that regulate this process in human cardiomyocytes remain to be elucidated. We hypothesized that doxorubicin significantly alters expression of genes involved in mitochondrial function in human cardiomyocytes, which in turn impairs mitochondrial respiration. Towards this, we treated human inducible pluripotent stem cell (iPSC)-cardiomyocytes with doxorubicin at 15 different time and dose conditions. Gene expression was assessed by RNAseq for each condition and 169 genes involved in mitochondrial function were analyzed for differential expression between control and treated conditions. Mitochondrial respiration (basal respiration, ATP production, maximal respiration, and spare respiratory capacity) was measured using the Seahorse Bioscience XFe96 Cell Mito Stress Test kit and correlated to gene expression levels. Of the 169 genes analyzed, 25 were significantly differentially expressed (P &lt; 0.05) including GPX4 (P = 5.70 x 10 -3 ). Expression of GPX4 remained significant in pairwise comparisons by dose for day 2 and qRT-PCR validation confirmed a dose-dependent decrease in GPX4 expression. Maximal respiration (r = -0.62; P = 0.031) and spare respiratory capacity (r = -0.67; P = 0.017) correlated with GPX4 expression in doxorubicin-treated iPSC-cardiomyocytes. GPX4 encodes a glutathione peroxidase that is responsible for protecting the cell against oxidative damage. Damage due to reactive oxygen species (ROS) is one of the established mechanisms of anthracycline-induced cardiac damage. Our findings underscore a role for mitochondrial function and ROS in the development of doxorubicin-induced cardiotoxicity and implicates GPX4 in this process. The assessment of doxorubicin-altered gene expression in iPSC-cardiomyocytes may provide insight into how impaired mitochondrial respiration leads to cardiotoxicity and heart failure in cancer survivors treated with doxorubicin and other anthracyclines. </jats:p

Economic and mental health impacts of multiple adverse events: Hurricane Harvey, other flooding events, and the COVID-19 pandemic

**Objectives** To assess the economic and mental health impacts of COVID-19 in the presence of previous exposure to flooding events. **Methods** Starting in April 2018, the Texas Flood Registry (TFR) invited residents to complete an online survey regarding their experiences with Hurricane Harvey and subsequent flooding events. Starting in April 2020, participants nationwide were invited to complete a brief online survey on their experiences during the pandemic. This study includes participants in the TFR (N = 20,754) and the COVID-19 Registry (N = 8568) through October 2020 (joint N = 2929). Logistic regression and generalized estimating equations were used to examine the relationship between exposure to flooding events and the economic and mental health impacts of COVID-19. **Results** Among COVID-19 registrants, 21% experienced moderate to severe anxiety during the pandemic, and 7% and 12% of households had difficulty paying rent and bills, respectively. Approximately 17% of Black and 15% of Hispanic households had difficulty paying rent, compared to 5% of non-Hispanic white households. The odds of COVID-19 income loss are 1.20 (1.02, 1.40) times higher for those who previously had storm-related home damage compared to those who did not and 3.84 (3.25–4.55) times higher for those who experienced Harvey income loss compared to those who did not. For registrants for whom Harvey was a severe impact event, the odds of having more severe anxiety during the pandemic are 5.14 (4.02, 6.58) times higher than among registrants for whom Harvey was a no meaningful impact event. **Conclusions** Multiple crises can jointly and cumulatively shape health and wellbeing outcomes. This knowledge can help craft emergency preparation and intervention program

Identifying High-Risk ZIP Codes for Childhood Lead Exposure: A Statewide ZCTA-Level Priority List for NorthCarolina.

BackgroundResearch has consistently shown that there is no safe blood lead level (BLL) for children. Despite progress in lead poisoning prevention, lead exposure remains a persistent threat to the health and neurological development of children. To identify high-risk ZIP codes for use by families and health care providers for the entire state of North Carolina, we developed a risk model using ZIP Code Tabula­tion Area (ZCTA)-level census data.MethodsWe obtained all available BLL testing data from the North Carolina Department of Health and Human Services for the years 2010–2015 via data use agreement. We fit a multivariable regression model with the ZCTA-level mean of log normalized BLLs as the de­pendent variable and ZCTA-level census data for known risk factors of childhood lead exposure as predictors. We used this model to create a priority risk categorization.ResultsWe organized ZCTAs into 20 quantiles, or priority risk categories, that can be used in local and statewide screening programs. The first six (of 20) quantiles were identified as particularly high-risk areas for childhood lead exposure.LimitationsBecause BLL testing is not universal, the BLL testing data used in this study are likely biased toward those most at risk for lead exposure.ConclusionThis study demonstrates the utility of ZCTA-level census data in identifying high-risk ZIP codes for childhood lead exposure, which can be used to ensure that the highest-risk children are tested in a timely manner. This approach can be replicated to address lead exposure nationally.</p